AI Engineer 5 ((AI Foundations, LLM Core and Agentic AI)
for section headings. Use - for any list of duties/requirements/benefits. Use
for prose.
We must not create sections with filler like "commensurate with experience". We have actual salary numbers, so Pay section is okay.
Benefits: we have statement about comprehensive benefits; we can include.
Schedule: no info, so omit.
We need to preserve all substantive information; not invent or summarize away detail. So we need to include details from Overview, Team Description, What You’ll Do, The Ideal Candidate, Basic Qualifications, Preferred Qualifications, Salary, Benefits.
We must not include boilerplate like "Capital One is an equal opportunity employer", etc. Also remove "No agencies please." etc. Also remove accommodation contact lines, etc. Also remove legal statements about criminal background, etc. Also remove "Capital One does not provide, endorse nor guarantee..." etc.
We need to keep the substantive content.
Let's extract:
Overview 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."
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: bullet list (but in text). Let's extract each duty:
- 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: list of traits:
- 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:
- 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:
- 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)
Salary info:
- Cambridge, MA: $229,900 - $262,400 for AI Engineer 5
- McLean, VA: $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.
Also mention: "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 include Benefits section with that prose.
Schedule: none.
We must not include duplicated lines. Ensure we don't repeat same content.
We need to output only HTML fragment, no markdown fences.
We'll structure:
About the role
Overview + Team Description combined? Could be two paragraphs.
Responsibilities
- ... each duty
Requirements
maybe for Basic Qualifications? Or we could split Requirements and Qualifications. The instruction says use headings for sections like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. So we need to map content.
We have Overview/Team Description -> About the role.
Responsibilities -> What You’ll Do.
Requirements -> Basic Qualifications? Or maybe Requirements = Basic Qualifications.
Qualifications -> Preferred Qualifications.
Skills -> maybe The Ideal Candidate traits? Could be Skills.
Benefits -> Benefits.
Pay -> Salary ranges + incentive.
Schedule -> omit.
We need to ensure we don't create empty sections.
Let's craft.
About the role: combine Overview and Team Description into maybe two elements.
Responsibilities: list each duty.
Requirements: Basic Qualifications (two bullet points). Could be
- ... or
- ... each.
Qualifications: Preferred Qualifications (list many).
Skills: The Ideal Candidate traits (list).
Benefits: paragraph about benefits.
Pay: paragraph about salary ranges and incentive compensation.
We must not include location-specific details? The salary info includes location-based ranges; we should include them as they are substantive. We'll include a
with the list.
We must not include "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." That's also substantive; we can include.
We must not include "This role is also eligible to earn performance based incentive compensation..." include.
We must not include "Learn more at the Capital One Careers website." maybe part of benefits.
We must not include "Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level." include in benefits.
Now ensure we don't include boilerplate like "Capital One is an equal opportunity employer", etc. Remove those.
Let's construct HTML.
We'll need to escape any special characters? Not needed.
We'll produce:
About the role
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.
The Intelligent Foundations and Experiences (IFX) team is at the center of
for prose. We must not create sections with filler like "commensurate with experience". We have actual salary numbers, so Pay section is okay. Benefits: we have statement about comprehensive benefits; we can include. Schedule: no info, so omit. We need to preserve all substantive information; not invent or summarize away detail. So we need to include details from Overview, Team Description, What You’ll Do, The Ideal Candidate, Basic Qualifications, Preferred Qualifications, Salary, Benefits. We must not include boilerplate like "Capital One is an equal opportunity employer", etc. Also remove "No agencies please." etc. Also remove accommodation contact lines, etc. Also remove legal statements about criminal background, etc. Also remove "Capital One does not provide, endorse nor guarantee..." etc. We need to keep the substantive content. Let's extract: Overview 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." 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: bullet list (but in text). Let's extract each duty: - 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: list of traits: - 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: - 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: - 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) Salary info: - Cambridge, MA: $229,900 - $262,400 for AI Engineer 5 - McLean, VA: $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. Also mention: "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 include Benefits section with that prose. Schedule: none. We must not include duplicated lines. Ensure we don't repeat same content. We need to output only HTML fragment, no markdown fences. We'll structure:
About the role
Overview + Team Description combined? Could be two paragraphs.
Responsibilities
- ... each duty
Requirements
maybe for Basic Qualifications? Or we could split Requirements and Qualifications. The instruction says use headings for sections like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. So we need to map content. We have Overview/Team Description -> About the role. Responsibilities -> What You’ll Do. Requirements -> Basic Qualifications? Or maybe Requirements = Basic Qualifications. Qualifications -> Preferred Qualifications. Skills -> maybe The Ideal Candidate traits? Could be Skills. Benefits -> Benefits. Pay -> Salary ranges + incentive. Schedule -> omit. We need to ensure we don't create empty sections. Let's craft. About the role: combine Overview and Team Description into maybe twoelements. Responsibilities: list each duty. Requirements: Basic Qualifications (two bullet points). Could be
- ... or
- ... each.
Qualifications: Preferred Qualifications (list many).
Skills: The Ideal Candidate traits (list).
Benefits: paragraph about benefits.
Pay: paragraph about salary ranges and incentive compensation.
We must not include location-specific details? The salary info includes location-based ranges; we should include them as they are substantive. We'll include a
with the list. We must not include "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." That's also substantive; we can include. We must not include "This role is also eligible to earn performance based incentive compensation..." include. We must not include "Learn more at the Capital One Careers website." maybe part of benefits. We must not include "Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level." include in benefits. Now ensure we don't include boilerplate like "Capital One is an equal opportunity employer", etc. Remove those. Let's construct HTML. We'll need to escape any special characters? Not needed. We'll produce:
About the role
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.
The Intelligent Foundations and Experiences (IFX) team is at the center of