AI Engineer 5 (MLX, Agentic AI, Gen AI platform Services)
for section headings. Use - for any list of duties/requirements/benefits, and
for prose.
We need to decide sections: About the role (maybe "About the role" or "Team Description"? The instruction: use headings e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. So we can map content.
We have: Team Description (could be About the role). What You'll Do (Responsibilities). The Ideal Candidate (maybe Requirements/Qualifications). Basic Qualifications (Qualifications). Preferred Qualifications (Skills? maybe also Qualifications). Pay (salary ranges). Benefits (benefits description). No schedule.
We need to avoid filler like "commensurate with experience". Not present.
We need to preserve all substantive info: include details about responsibilities list items, qualifications list items, etc.
We must not invent or summarize away detail. So we need to keep the bullet points as they appear.
Let's extract content.
First paragraph: "At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build."
That's prose about role/company.
Team Description: "The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact."
What You'll Do: list bullet points:
- Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.
- Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.
- Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more.
- Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems.
- Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.
- Design, implement and optimize multi-model orchestration pipelines - integrating LLMs, vector search, and domain-specific models into unified systems
- Establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency
- Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards
- Mentor Principal and Manager-level AI engineers, fostering cross-domain learning and elevating organizational technical maturity
The Ideal Candidate: prose bullet list? Actually it's a paragraph with bullet-like sentences. We'll treat as list items.
- You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing.
- You want to work on problems that will help change banking for good
- Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production
- You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity.
- You have the courage to share new ideas even when they are unproven
- You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss
- You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown
Basic Qualifications: list:
- Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies
- At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java
Preferred Qualifications: list many items:
- Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy
- 7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)
- Experience designing, developing, delivering, and supporting complex AI systems
- Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang
- Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost
- Experience in building agentic AI systems and agentic workflows
- Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production
- Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers
- Experience architecting and integrating heterogeneous AI systems - including rule-based, retrieval-augmented, and generative components - into unified production pipelines
- Experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes
- Demonstrated ability to balance model performance and operational cost through dynamic inference strategies and model compression
- Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs)
Pay: salary ranges per location:
- McLean, VA: $229,900 - $262,400 for AI Engineer 5
- Cambridge, MA: $229,900 - $262,400 for AI Engineer 5
- New York, NY: $250,800 - $286,200 for AI Engineer 5
- San Francisco, CA: $250,800 - $286,200 for AI Engineer 5
- San Jose, CA: $250,800 - $286,200 for AI Engineer 5
- Note about other locations: candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter.
- This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.
Benefits: "Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level."
We should keep that as benefits.
We must not include boilerplate like EEO, legal, accommodation, etc. Remove those paragraphs.
Now produce HTML.
Structure:
About the role
... (the first paragraph + Team Description? Actually Team Description could be separate heading "Team Description" but not in allowed list. Could merge into About the role. Probably better to have About the role includes the introductory paragraph and Team Description. Or we could have separate headings: About the role and Team Description? The instruction says use headings e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. It doesn't forbid other headings but says use those for section headings. It says "use
for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule)." That suggests we should use those headings where appropriate. We can also have other headings? It says use for section headings (e.g. ...). Likely they expect only those headings. So we should map content to those headings.
Thus:
- About the role: include introductory paragraph and Team Description.
- Responsibilities: What You'll Do.
- Requirements: maybe Basic Qualifications? Or Requirements could be Basic Qualifications.
- Qualifications: maybe Preferred Qualifications? Or Skills? The list includes Qualifications and Skills. We could put Basic Qualifications under Requirements, Preferred Qualifications under Skills, or Qualifications. Let's decide: Use Requirements for Basic Qualifications, Skills for Preferred Qualifications. Or we could have Qualifications for both basic and preferred? But we need to avoid thin sections. We'll do:
About the role
... (intro + team description)
Responsibilities
...
Requirements
... (Basic Qualifications)
Skills
... (Preferred Qualifications)
Pay
... (salary ranges)
Benefits
... (benefits description)
We should not include Schedule.
Now ensure we preserve all substantive info. For About the role we need to include both the introductory paragraph and Team Description. We'll combine them into one maybe with two sentences? Better to keep as one paragraph containing both. Could separate into two
but that's okay. We'll just put them in one
separated by a space.
Now Responsibilities: list each bullet as
- . Ensure we keep the exact wording.
Requirements: Basic Qualifications two items. Each as
- .
Skills: Preferred Qualifications many items. Each as
- .
Pay: list each location as
- . Also include note about other locations and incentive compensation. Could be separate
- items.
Benefits:
with the benefits description.
Now check for any boilerplate we inadvertently kept: The sentence "Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level." That's fine.
We removed EEO etc.
Now produce HTML.
Be careful to not include markdown
for prose. We need to decide sections: About the role (maybe "About the role" or "Team Description"? The instruction: use headings e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. So we can map content. We have: Team Description (could be About the role). What You'll Do (Responsibilities). The Ideal Candidate (maybe Requirements/Qualifications). Basic Qualifications (Qualifications). Preferred Qualifications (Skills? maybe also Qualifications). Pay (salary ranges). Benefits (benefits description). No schedule. We need to avoid filler like "commensurate with experience". Not present. We need to preserve all substantive info: include details about responsibilities list items, qualifications list items, etc. We must not invent or summarize away detail. So we need to keep the bullet points as they appear. Let's extract content. First paragraph: "At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build." That's prose about role/company. Team Description: "The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact." What You'll Do: list bullet points: - Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. - Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. - Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. - Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems. - Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. - Design, implement and optimize multi-model orchestration pipelines - integrating LLMs, vector search, and domain-specific models into unified systems - Establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency - Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards - Mentor Principal and Manager-level AI engineers, fostering cross-domain learning and elevating organizational technical maturity The Ideal Candidate: prose bullet list? Actually it's a paragraph with bullet-like sentences. We'll treat as list items. - You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. - You want to work on problems that will help change banking for good - Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production - You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. - You have the courage to share new ideas even when they are unproven - You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss - You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: list: - Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies - At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: list many items: - Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy - 7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) - Experience designing, developing, delivering, and supporting complex AI systems - Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang - Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost - Experience in building agentic AI systems and agentic workflows - Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production - Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers - Experience architecting and integrating heterogeneous AI systems - including rule-based, retrieval-augmented, and generative components - into unified production pipelines - Experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes - Demonstrated ability to balance model performance and operational cost through dynamic inference strategies and model compression - Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) Pay: salary ranges per location: - McLean, VA: $229,900 - $262,400 for AI Engineer 5 - Cambridge, MA: $229,900 - $262,400 for AI Engineer 5 - New York, NY: $250,800 - $286,200 for AI Engineer 5 - San Francisco, CA: $250,800 - $286,200 for AI Engineer 5 - San Jose, CA: $250,800 - $286,200 for AI Engineer 5 - Note about other locations: candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. - This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Benefits: "Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level." We should keep that as benefits. We must not include boilerplate like EEO, legal, accommodation, etc. Remove those paragraphs. Now produce HTML. Structure:
About the role
... (the first paragraph + Team Description? Actually Team Description could be separate heading "Team Description" but not in allowed list. Could merge into About the role. Probably better to have About the role includes the introductory paragraph and Team Description. Or we could have separate headings: About the role and Team Description? The instruction says use headings e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. It doesn't forbid other headings but says use those for section headings. It says "use
for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule)." That suggests we should use those headings where appropriate. We can also have other headings? It says use for section headings (e.g. ...). Likely they expect only those headings. So we should map content to those headings.
Thus:
- About the role: include introductory paragraph and Team Description.
- Responsibilities: What You'll Do.
- Requirements: maybe Basic Qualifications? Or Requirements could be Basic Qualifications.
- Qualifications: maybe Preferred Qualifications? Or Skills? The list includes Qualifications and Skills. We could put Basic Qualifications under Requirements, Preferred Qualifications under Skills, or Qualifications. Let's decide: Use Requirements for Basic Qualifications, Skills for Preferred Qualifications. Or we could have Qualifications for both basic and preferred? But we need to avoid thin sections. We'll do:
About the role
About the role
... (intro + team description)
Responsibilities
- ...
Requirements
- ... (Basic Qualifications)
Skills
- ... (Preferred Qualifications)
Pay
- ... (salary ranges)
Benefits
... (benefits description)
We should not include Schedule. Now ensure we preserve all substantive info. For About the role we need to include both the introductory paragraph and Team Description. We'll combine them into onemaybe with two sentences? Better to keep as one paragraph containing both. Could separate into two
but that's okay. We'll just put them in one
separated by a space. Now Responsibilities: list each bullet as
with the benefits description. Now check for any boilerplate we inadvertently kept: The sentence "Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level." That's fine. We removed EEO etc. Now produce HTML. Be careful to not include markdown