Director of Applied Research
for section headings. Use - for any list of duties/requirements/benefits, and
for prose. Include a section only when posting has real, specific content. Remove boilerplate: cookie/navigation/legal/EEO/equal-opportunity/scam-warning, duplicated lines, application instructions. Also remove "This job posting will close 01/31/2027." maybe considered application instruction? It's a date; could be considered metadata but not essential; we can drop. Also "About Us" at end truncated; we can include if substantive? It's truncated: "About Us Thomson Reuters informs the way forward by bringing together the trusted content and technology that people and organizations need to make the right decisions. We serve prof". That's incomplete; maybe we drop as it's boilerplate/truncated. We'll keep only substantive sections.
We need to preserve all substantive information; not invent or summarize away detail. So we need to include details from each section.
Let's extract:
- About Thomson Reuters Labs: paragraph(s). We'll put under heading "About the Labs" maybe? The instruction says use headings like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. But we can also use other headings? It says use
for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). It suggests those are examples; we can use those headings if appropriate. For "About Thomson Reuters Labs", we could use "About the role" or maybe "About the Labs". But they said do NOT repeat the job title as a heading. The job title is "Director of Applied Research, Information Retrieval". So we can use "About the role" as heading for the description about the role/labs. That seems okay.
- Key Responsibilities: multiple bullet-like paragraphs. We'll create a - list.
- Required Qualifications: includes Education & Experience, Leadership & Team Building, Technical Expertise. We'll maybe split into subheadings? But instruction says prefer few substantive sections over many thin ones. Could combine all qualifications into one section "Requirements" or "Qualifications". Use
for Requirements. Then inside we can have paragraphs and lists.
- Ideal Candidate Profile: could be part of "Skills" or "Qualifications". Might be separate "Skills". We'll treat as "Skills".
- Preferred Qualifications: could be another "Qualifications" but we can merge into same section? Might be separate "Preferred Qualifications". But instruction says prefer few sections; we could have "Qualifications" covering both required and preferred, but we need to preserve distinction? Might be okay to have separate subheadings inside? Not required to use headings inside; we can just have paragraphs.
- What’s in it For You?: includes Flexibility & Work-Life Balance, Career Development and Growth, Industry Competitive Benefits, Culture, Social Impact, Making a Real-World Impact, plus US benefits details. That's benefits. We'll create a Benefits section with lists.
- Pay: The posting includes base compensation range $198,200 USD - $368,000 USD. Also mentions annual bonus eligibility. We'll create a Pay section with that info.
- Schedule: Not mentioned explicitly; flexible work arrangements, work from anywhere up to 8 weeks per year. That's schedule/flexibility. Could be part of Benefits or Schedule. Since they said include Schedule section only if posting actually states them. It does mention flexible work arrangements, work from anywhere up to 8 weeks per year. That's schedule info. We'll create a Schedule section.
We must not include boilerplate like "Flex My Way is a set of supportive workplace policies..." but that's part of benefits; we keep.
We must not include duplicated lines. Ensure we don't repeat.
Now craft HTML.
Structure:
About the role
Thomson Reuters Labs ... (the paragraph about labs).
Responsibilities
- Define Technical Vision & Strategy: ... (the bullet points). We need to break each bullet into
- . The responsibilities section has headings like "Define Technical Vision & Strategy", "Build & Lead a High-Performing Team", etc. We'll treat each as a list item with its subpoints maybe as separate sentences inside
- . Could also nest
but not required. We'll keep simple.
We need to preserve all substantive information; we can include the sub-bullets as part of the - text.
Let's extract each responsibility block:
1. Define Technical Vision & Strategy
- Set the strategic direction for Information Retrieval research and innovation at Thomson Reuters, positioning TR as a leader in retrieval-based AI
- Establish the technical direction for retrieval, ranking, semantic search, retrieval-augmented generation (RAG), and agentic retrieval system capabilities
- Design and optimize retrieval architectures leveraging embeddings, reranking, hybrid search, knowledge graphs, and contextual retrieval techniques
- Build evaluation frameworks and benchmarks for search quality, relevance, answer quality, and real-world business impact
- Contribute to the global TR Labs engineering strategy and methodology through adoption of emerging AI/ML technologies and industry best practices
2. Build & Lead a High-Performing Team
- Hire, train, and manage a highly skilled team with expertise across cloud engineering, machine learning engineering, data engineering, and AI research
- Mentor scientists and engineers while establishing best practices for production AI development and deployment
- Foster a culture of collaboration, innovation, and continuous learning across the global labs organization
- Develop team members' technical depth in information retrieval, NLP, generative AI, and large-scale AI systems
3. Drive Production AI Solutions
- Lead development of enterprise-grade retrieval, ranking, NLP, and knowledge-based AI solutions that integrate with Thomson Reuters products
- Partner closely with Product and Engineering teams to translate customer needs and domain-specific challenges into scalable AI applications
- Establish robust channels between Labs research and product technology organizations, enabling effective transfer of innovation to production systems
- Apply modern development practices across the entire software development lifecycle—from experimentation to deployment to operational excellence
- Demonstrate proficiency in automation, system monitoring, MLOps, and cloud-native AI applications on AWS, Azure, or equivalent platforms
4. Drive Strategy & Business Impact
- Proactively identify opportunities where Labs can improve the status quo or generate new business value through AI/ML innovation
- Influence the global project portfolio and investment decisions with your expertise in applied AI and domain knowledge
- Provide strategic input to product and modernization roadmaps, particularly in identifying and articulating AI-driven opportunities
- Translate complex customer problems in legal, tax, news, and corporate domains into successful AI solutions
- Continuously question why something needs to be done and for whom, maintaining a strong customer-centric mindset
5. Be a Trusted Advisor
- Actively engage across cross-functional teams, sharing knowledge, valuing diverse ideas, and building relationships with technology and product leaders
- Communicate effectively—translating between research and engineering methodologies and languages
- Secure alignment and clear paths to market for AI-powered initiatives
We'll put each as
- with the heading bold? Not needed; just plain text.
Requirements
We need to include Education & Experience, Leadership & Team Building, Technical Expertise.
We'll create for each subsection maybe.
Education & Experience:
- PhD in Computer Science, Artificial Intelligence, Machine Learning, Natural Language Processing, Information Retrieval, or a closely related field
- 8+ years of industry experience building and deploying production AI systems at scale
- Proven track record of successfully taking machine learning and AI solutions from research to production-grade software with measurable business impact
- A strong publication record in leading venues such as SIGIR, NeurIPS, ICLR, ACL, EMNLP, KDD, WWW, or comparable conferences
Leadership & Team Building:
- Demonstrated ability to build, mentor, and manage high-performing teams of engineers and scientists
- Experience leading cross-functional initiatives and influencing technical strategy across research, engineering, and product organizations
- An entrepreneurial mindset with confidence in making independent decisions and driving initiatives forward
- Exceptional communication, collaboration, and stakeholder management skills
Technical Expertise:
- Information Retrieval & Search: Semantic search, ranking algorithms, retrieval optimization, search relevance, and evaluation methodologies
- Retrieval-Augmented Generation (RAG): Design and optimization of RAG systems, grounding techniques, and answer quality assurance
- Agentic Retrieval Systems: Tool-using retrieval agents, multi-step reasoning for search, and autonomous information discovery
- Natural Language Processing: Core NLP tasks including Named Entity Recognition (NER), Information Extraction, question answering, and advanced language understanding
- Large Language Models & Generative AI: Prompt engineering, fine-tuning, model evaluation, and production deployment of LLM-based applications
- Knowledge Graphs & Knowledge Systems: Design, construction, and leveraging of knowledge graphs for AI applications
- Production AI Development: Hands-on experience with Python, PyTorch, Hugging Face, and modern MLOps practices
- Cloud-Native AI: Proficiency in AWS, Azure, or equivalent cloud platforms for deploying and operating AI solutions at scale
- Emerging Technologies: A demonstrated desire to learn and embrace new and emerging technologies in the AI/ML landscape
We'll put each as
- under appropriate headings? Could just list all as
- but better to group.
We could have
Requirements
then Education & Experience:
... etc.
Similarly for Skills (Ideal Candidate Profile) and Preferred Qualifications.
Skills
Ideal Candidate Profile bullet points:
- You understand and can translate between research and engineering languages and methodologies
- You bring a strong product mindset and understand how to translate complex customer problems into successful solutions
- You have a fundamental understanding of the SDLC and hands-on experience in programming languages such as Python, Java, TypeScript, or JavaScript
- You are comfortable with ambiguity, creative in redirecting when reaching dead ends, and embrace continuous evolution of your skills
- You thrive in diverse, agile, and interdisciplinary environments with a strong sense of urgency
We'll list as - .
Preferred Qualifications
List:
- Experience building enterprise search, discovery, or research-assistance platforms
- Experience within Legal, Tax & Accounting, Risk, Financial Services, or other complex professional domains
- Experience with hybrid search, vector databases, recommendation systems, and large-scale retrieval platforms
- Experience deploying and operating AI solutions using Azure ML, Azure AI Foundry, AWS SageMaker, or similar cloud platforms
- Experience leading large-scale AI initiatives and building diverse, geographically distributed teams
- Familiarity with MLOps frameworks, containerization, and modern DevOps practices for AI systems
Benefits
We need to capture all benefits details.
From "What’s in it For You?":
Flexibility & Work-Life Balance: Flex My Way is a set of supportive workplace policies designed to help manage personal and professional responsibilities, whether caring for family, giving back to the community, or finding time to refresh and reset. This builds upon our flexible work arrangements, including work from anywhere for up to 8 weeks per year, empowering employees to achieve a better work-life balance.
Career Development and Growth: By fostering a culture of continuous learning and skill development, we prepare our talent to tackle tomorrow’s challenges and deliver real-world solutions. Our Grow My Way programming and skills-first approach ensures you have the tools and knowledge to grow, lead, and thrive in an AI-enabled future.
Industry Competitive Benefits: We offer comprehensive benefit plans to include flexible vacation, two company-wide Mental Health Days off, access to the
for prose. Include a section only when posting has real, specific content. Remove boilerplate: cookie/navigation/legal/EEO/equal-opportunity/scam-warning, duplicated lines, application instructions. Also remove "This job posting will close 01/31/2027." maybe considered application instruction? It's a date; could be considered metadata but not essential; we can drop. Also "About Us" at end truncated; we can include if substantive? It's truncated: "About Us Thomson Reuters informs the way forward by bringing together the trusted content and technology that people and organizations need to make the right decisions. We serve prof". That's incomplete; maybe we drop as it's boilerplate/truncated. We'll keep only substantive sections. We need to preserve all substantive information; not invent or summarize away detail. So we need to include details from each section. Let's extract: - About Thomson Reuters Labs: paragraph(s). We'll put under heading "About the Labs" maybe? The instruction says use headings like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. But we can also use other headings? It says use
for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). It suggests those are examples; we can use those headings if appropriate. For "About Thomson Reuters Labs", we could use "About the role" or maybe "About the Labs". But they said do NOT repeat the job title as a heading. The job title is "Director of Applied Research, Information Retrieval". So we can use "About the role" as heading for the description about the role/labs. That seems okay.
- Key Responsibilities: multiple bullet-like paragraphs. We'll create a - list.
- Required Qualifications: includes Education & Experience, Leadership & Team Building, Technical Expertise. We'll maybe split into subheadings? But instruction says prefer few substantive sections over many thin ones. Could combine all qualifications into one section "Requirements" or "Qualifications". Use
for Requirements. Then inside we can have paragraphs and lists.
- Ideal Candidate Profile: could be part of "Skills" or "Qualifications". Might be separate "Skills". We'll treat as "Skills".
- Preferred Qualifications: could be another "Qualifications" but we can merge into same section? Might be separate "Preferred Qualifications". But instruction says prefer few sections; we could have "Qualifications" covering both required and preferred, but we need to preserve distinction? Might be okay to have separate subheadings inside? Not required to use headings inside; we can just have paragraphs.
- What’s in it For You?: includes Flexibility & Work-Life Balance, Career Development and Growth, Industry Competitive Benefits, Culture, Social Impact, Making a Real-World Impact, plus US benefits details. That's benefits. We'll create a Benefits section with lists.
- Pay: The posting includes base compensation range $198,200 USD - $368,000 USD. Also mentions annual bonus eligibility. We'll create a Pay section with that info.
- Schedule: Not mentioned explicitly; flexible work arrangements, work from anywhere up to 8 weeks per year. That's schedule/flexibility. Could be part of Benefits or Schedule. Since they said include Schedule section only if posting actually states them. It does mention flexible work arrangements, work from anywhere up to 8 weeks per year. That's schedule info. We'll create a Schedule section.
We must not include boilerplate like "Flex My Way is a set of supportive workplace policies..." but that's part of benefits; we keep.
We must not include duplicated lines. Ensure we don't repeat.
Now craft HTML.
Structure:
About the role
Thomson Reuters Labs ... (the paragraph about labs).
Responsibilities
- Define Technical Vision & Strategy: ... (the bullet points). We need to break each bullet into
- . The responsibilities section has headings like "Define Technical Vision & Strategy", "Build & Lead a High-Performing Team", etc. We'll treat each as a list item with its subpoints maybe as separate sentences inside
- . Could also nest
but not required. We'll keep simple.
We need to preserve all substantive information; we can include the sub-bullets as part of the - text.
Let's extract each responsibility block:
1. Define Technical Vision & Strategy
- Set the strategic direction for Information Retrieval research and innovation at Thomson Reuters, positioning TR as a leader in retrieval-based AI
- Establish the technical direction for retrieval, ranking, semantic search, retrieval-augmented generation (RAG), and agentic retrieval system capabilities
- Design and optimize retrieval architectures leveraging embeddings, reranking, hybrid search, knowledge graphs, and contextual retrieval techniques
- Build evaluation frameworks and benchmarks for search quality, relevance, answer quality, and real-world business impact
- Contribute to the global TR Labs engineering strategy and methodology through adoption of emerging AI/ML technologies and industry best practices
2. Build & Lead a High-Performing Team
- Hire, train, and manage a highly skilled team with expertise across cloud engineering, machine learning engineering, data engineering, and AI research
- Mentor scientists and engineers while establishing best practices for production AI development and deployment
- Foster a culture of collaboration, innovation, and continuous learning across the global labs organization
- Develop team members' technical depth in information retrieval, NLP, generative AI, and large-scale AI systems
3. Drive Production AI Solutions
- Lead development of enterprise-grade retrieval, ranking, NLP, and knowledge-based AI solutions that integrate with Thomson Reuters products
- Partner closely with Product and Engineering teams to translate customer needs and domain-specific challenges into scalable AI applications
- Establish robust channels between Labs research and product technology organizations, enabling effective transfer of innovation to production systems
- Apply modern development practices across the entire software development lifecycle—from experimentation to deployment to operational excellence
- Demonstrate proficiency in automation, system monitoring, MLOps, and cloud-native AI applications on AWS, Azure, or equivalent platforms
4. Drive Strategy & Business Impact
- Proactively identify opportunities where Labs can improve the status quo or generate new business value through AI/ML innovation
- Influence the global project portfolio and investment decisions with your expertise in applied AI and domain knowledge
- Provide strategic input to product and modernization roadmaps, particularly in identifying and articulating AI-driven opportunities
- Translate complex customer problems in legal, tax, news, and corporate domains into successful AI solutions
- Continuously question why something needs to be done and for whom, maintaining a strong customer-centric mindset
5. Be a Trusted Advisor
- Actively engage across cross-functional teams, sharing knowledge, valuing diverse ideas, and building relationships with technology and product leaders
- Communicate effectively—translating between research and engineering methodologies and languages
- Secure alignment and clear paths to market for AI-powered initiatives
We'll put each as
- with the heading bold? Not needed; just plain text.
Requirements
We need to include Education & Experience, Leadership & Team Building, Technical Expertise.
We'll create for each subsection maybe.
Education & Experience:
- PhD in Computer Science, Artificial Intelligence, Machine Learning, Natural Language Processing, Information Retrieval, or a closely related field
- 8+ years of industry experience building and deploying production AI systems at scale
- Proven track record of successfully taking machine learning and AI solutions from research to production-grade software with measurable business impact
- A strong publication record in leading venues such as SIGIR, NeurIPS, ICLR, ACL, EMNLP, KDD, WWW, or comparable conferences
Leadership & Team Building:
- Demonstrated ability to build, mentor, and manage high-performing teams of engineers and scientists
- Experience leading cross-functional initiatives and influencing technical strategy across research, engineering, and product organizations
- An entrepreneurial mindset with confidence in making independent decisions and driving initiatives forward
- Exceptional communication, collaboration, and stakeholder management skills
Technical Expertise:
- Information Retrieval & Search: Semantic search, ranking algorithms, retrieval optimization, search relevance, and evaluation methodologies
- Retrieval-Augmented Generation (RAG): Design and optimization of RAG systems, grounding techniques, and answer quality assurance
- Agentic Retrieval Systems: Tool-using retrieval agents, multi-step reasoning for search, and autonomous information discovery
- Natural Language Processing: Core NLP tasks including Named Entity Recognition (NER), Information Extraction, question answering, and advanced language understanding
- Large Language Models & Generative AI: Prompt engineering, fine-tuning, model evaluation, and production deployment of LLM-based applications
- Knowledge Graphs & Knowledge Systems: Design, construction, and leveraging of knowledge graphs for AI applications
- Production AI Development: Hands-on experience with Python, PyTorch, Hugging Face, and modern MLOps practices
- Cloud-Native AI: Proficiency in AWS, Azure, or equivalent cloud platforms for deploying and operating AI solutions at scale
- Emerging Technologies: A demonstrated desire to learn and embrace new and emerging technologies in the AI/ML landscape
We'll put each as
- under appropriate headings? Could just list all as
- but better to group.
We could have
Requirements
then Education & Experience:
... etc.
Similarly for Skills (Ideal Candidate Profile) and Preferred Qualifications.
Skills
Ideal Candidate Profile bullet points:
- You understand and can translate between research and engineering languages and methodologies
- You bring a strong product mindset and understand how to translate complex customer problems into successful solutions
- You have a fundamental understanding of the SDLC and hands-on experience in programming languages such as Python, Java, TypeScript, or JavaScript
- You are comfortable with ambiguity, creative in redirecting when reaching dead ends, and embrace continuous evolution of your skills
- You thrive in diverse, agile, and interdisciplinary environments with a strong sense of urgency
We'll list as - .
Preferred Qualifications
List:
- Experience building enterprise search, discovery, or research-assistance platforms
- Experience within Legal, Tax & Accounting, Risk, Financial Services, or other complex professional domains
- Experience with hybrid search, vector databases, recommendation systems, and large-scale retrieval platforms
- Experience deploying and operating AI solutions using Azure ML, Azure AI Foundry, AWS SageMaker, or similar cloud platforms
- Experience leading large-scale AI initiatives and building diverse, geographically distributed teams
- Familiarity with MLOps frameworks, containerization, and modern DevOps practices for AI systems
Benefits
We need to capture all benefits details.
From "What’s in it For You?":
Flexibility & Work-Life Balance: Flex My Way is a set of supportive workplace policies designed to help manage personal and professional responsibilities, whether caring for family, giving back to the community, or finding time to refresh and reset. This builds upon our flexible work arrangements, including work from anywhere for up to 8 weeks per year, empowering employees to achieve a better work-life balance.
Career Development and Growth: By fostering a culture of continuous learning and skill development, we prepare our talent to tackle tomorrow’s challenges and deliver real-world solutions. Our Grow My Way programming and skills-first approach ensures you have the tools and knowledge to grow, lead, and thrive in an AI-enabled future.
Industry Competitive Benefits: We offer comprehensive benefit plans to include flexible vacation, two company-wide Mental Health Days off, access to the
for Requirements. Then inside we can have paragraphs and lists.
- Ideal Candidate Profile: could be part of "Skills" or "Qualifications". Might be separate "Skills". We'll treat as "Skills".
- Preferred Qualifications: could be another "Qualifications" but we can merge into same section? Might be separate "Preferred Qualifications". But instruction says prefer few sections; we could have "Qualifications" covering both required and preferred, but we need to preserve distinction? Might be okay to have separate subheadings inside? Not required to use headings inside; we can just have paragraphs.
- What’s in it For You?: includes Flexibility & Work-Life Balance, Career Development and Growth, Industry Competitive Benefits, Culture, Social Impact, Making a Real-World Impact, plus US benefits details. That's benefits. We'll create a Benefits section with lists.
- Pay: The posting includes base compensation range $198,200 USD - $368,000 USD. Also mentions annual bonus eligibility. We'll create a Pay section with that info.
- Schedule: Not mentioned explicitly; flexible work arrangements, work from anywhere up to 8 weeks per year. That's schedule/flexibility. Could be part of Benefits or Schedule. Since they said include Schedule section only if posting actually states them. It does mention flexible work arrangements, work from anywhere up to 8 weeks per year. That's schedule info. We'll create a Schedule section.
We must not include boilerplate like "Flex My Way is a set of supportive workplace policies..." but that's part of benefits; we keep.
We must not include duplicated lines. Ensure we don't repeat.
Now craft HTML.
Structure:
About the role
Thomson Reuters Labs ... (the paragraph about labs).
Responsibilities
- Define Technical Vision & Strategy: ... (the bullet points). We need to break each bullet into
- . The responsibilities section has headings like "Define Technical Vision & Strategy", "Build & Lead a High-Performing Team", etc. We'll treat each as a list item with its subpoints maybe as separate sentences inside
- . Could also nest
- but not required. We'll keep simple.
We need to preserve all substantive information; we can include the sub-bullets as part of the
- text. Let's extract each responsibility block: 1. Define Technical Vision & Strategy - Set the strategic direction for Information Retrieval research and innovation at Thomson Reuters, positioning TR as a leader in retrieval-based AI - Establish the technical direction for retrieval, ranking, semantic search, retrieval-augmented generation (RAG), and agentic retrieval system capabilities - Design and optimize retrieval architectures leveraging embeddings, reranking, hybrid search, knowledge graphs, and contextual retrieval techniques - Build evaluation frameworks and benchmarks for search quality, relevance, answer quality, and real-world business impact - Contribute to the global TR Labs engineering strategy and methodology through adoption of emerging AI/ML technologies and industry best practices 2. Build & Lead a High-Performing Team - Hire, train, and manage a highly skilled team with expertise across cloud engineering, machine learning engineering, data engineering, and AI research - Mentor scientists and engineers while establishing best practices for production AI development and deployment - Foster a culture of collaboration, innovation, and continuous learning across the global labs organization - Develop team members' technical depth in information retrieval, NLP, generative AI, and large-scale AI systems 3. Drive Production AI Solutions - Lead development of enterprise-grade retrieval, ranking, NLP, and knowledge-based AI solutions that integrate with Thomson Reuters products - Partner closely with Product and Engineering teams to translate customer needs and domain-specific challenges into scalable AI applications - Establish robust channels between Labs research and product technology organizations, enabling effective transfer of innovation to production systems - Apply modern development practices across the entire software development lifecycle—from experimentation to deployment to operational excellence - Demonstrate proficiency in automation, system monitoring, MLOps, and cloud-native AI applications on AWS, Azure, or equivalent platforms 4. Drive Strategy & Business Impact - Proactively identify opportunities where Labs can improve the status quo or generate new business value through AI/ML innovation - Influence the global project portfolio and investment decisions with your expertise in applied AI and domain knowledge - Provide strategic input to product and modernization roadmaps, particularly in identifying and articulating AI-driven opportunities - Translate complex customer problems in legal, tax, news, and corporate domains into successful AI solutions - Continuously question why something needs to be done and for whom, maintaining a strong customer-centric mindset 5. Be a Trusted Advisor - Actively engage across cross-functional teams, sharing knowledge, valuing diverse ideas, and building relationships with technology and product leaders - Communicate effectively—translating between research and engineering methodologies and languages - Secure alignment and clear paths to market for AI-powered initiatives We'll put each as
- with the heading bold? Not needed; just plain text.
Requirements
We need to include Education & Experience, Leadership & Team Building, Technical Expertise. We'll createfor each subsection maybe. Education & Experience: - PhD in Computer Science, Artificial Intelligence, Machine Learning, Natural Language Processing, Information Retrieval, or a closely related field - 8+ years of industry experience building and deploying production AI systems at scale - Proven track record of successfully taking machine learning and AI solutions from research to production-grade software with measurable business impact - A strong publication record in leading venues such as SIGIR, NeurIPS, ICLR, ACL, EMNLP, KDD, WWW, or comparable conferences Leadership & Team Building: - Demonstrated ability to build, mentor, and manage high-performing teams of engineers and scientists - Experience leading cross-functional initiatives and influencing technical strategy across research, engineering, and product organizations - An entrepreneurial mindset with confidence in making independent decisions and driving initiatives forward - Exceptional communication, collaboration, and stakeholder management skills Technical Expertise: - Information Retrieval & Search: Semantic search, ranking algorithms, retrieval optimization, search relevance, and evaluation methodologies - Retrieval-Augmented Generation (RAG): Design and optimization of RAG systems, grounding techniques, and answer quality assurance - Agentic Retrieval Systems: Tool-using retrieval agents, multi-step reasoning for search, and autonomous information discovery - Natural Language Processing: Core NLP tasks including Named Entity Recognition (NER), Information Extraction, question answering, and advanced language understanding - Large Language Models & Generative AI: Prompt engineering, fine-tuning, model evaluation, and production deployment of LLM-based applications - Knowledge Graphs & Knowledge Systems: Design, construction, and leveraging of knowledge graphs for AI applications - Production AI Development: Hands-on experience with Python, PyTorch, Hugging Face, and modern MLOps practices - Cloud-Native AI: Proficiency in AWS, Azure, or equivalent cloud platforms for deploying and operating AI solutions at scale - Emerging Technologies: A demonstrated desire to learn and embrace new and emerging technologies in the AI/ML landscape We'll put each as
- under appropriate headings? Could just list all as
- but better to group.
We could have
Requirements
thenEducation & Experience:
- ... etc.
Similarly for Skills (Ideal Candidate Profile) and Preferred Qualifications.
- .
Preferred Qualifications
List: - Experience building enterprise search, discovery, or research-assistance platforms - Experience within Legal, Tax & Accounting, Risk, Financial Services, or other complex professional domains - Experience with hybrid search, vector databases, recommendation systems, and large-scale retrieval platforms - Experience deploying and operating AI solutions using Azure ML, Azure AI Foundry, AWS SageMaker, or similar cloud platforms - Experience leading large-scale AI initiatives and building diverse, geographically distributed teams - Familiarity with MLOps frameworks, containerization, and modern DevOps practices for AI systemsBenefits
We need to capture all benefits details. From "What’s in it For You?": Flexibility & Work-Life Balance: Flex My Way is a set of supportive workplace policies designed to help manage personal and professional responsibilities, whether caring for family, giving back to the community, or finding time to refresh and reset. This builds upon our flexible work arrangements, including work from anywhere for up to 8 weeks per year, empowering employees to achieve a better work-life balance. Career Development and Growth: By fostering a culture of continuous learning and skill development, we prepare our talent to tackle tomorrow’s challenges and deliver real-world solutions. Our Grow My Way programming and skills-first approach ensures you have the tools and knowledge to grow, lead, and thrive in an AI-enabled future. Industry Competitive Benefits: We offer comprehensive benefit plans to include flexible vacation, two company-wide Mental Health Days off, access to the
Skills
Ideal Candidate Profile bullet points: - You understand and can translate between research and engineering languages and methodologies - You bring a strong product mindset and understand how to translate complex customer problems into successful solutions - You have a fundamental understanding of the SDLC and hands-on experience in programming languages such as Python, Java, TypeScript, or JavaScript - You are comfortable with ambiguity, creative in redirecting when reaching dead ends, and embrace continuous evolution of your skills - You thrive in diverse, agile, and interdisciplinary environments with a strong sense of urgency We'll list as - .