Lead AI Engineer (AI Foundations)
Capital One · Cambridge, MA · 1 mo ago
Information Technology$197k–$225k/yrFull-time
We need to output HTML fragment with sections: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Only include sections that have real specific content. The posting includes overview, team description, responsibilities (In this role, you will: ...), Ideal Candidate (qualities), Basic Qualifications, Preferred Qualifications, Salary info, Benefits mention, maybe schedule not mentioned. No explicit schedule. Benefits: mention comprehensive benefits, but not details. Should we include Benefits section? The instruction: include a section ONLY when posting has real, specific content for it — never emit a heading followed by filler/placeholder text (e.g. "commensurate with experience", "not specified", "N/A", "varies", "TBD") and never create Pay/Schedule/Benefits sections unless the posting actually states them. The posting says: "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." That's somewhat generic but still states benefits exist. Is that considered specific enough? It says "comprehensive, competitive, and inclusive set of health, financial and other benefits". That's somewhat vague but still mentions benefits. Might be acceptable to include Benefits section with that sentence. Pay: they give salary ranges per location. That's specific. So include Pay section. Schedule: not mentioned, so omit.
Sections we can have: About the role (overview + team description), Responsibilities (the bullet list), Requirements (maybe Basic Qualifications?), Qualifications (Preferred Qualifications?), Skills (maybe technical skills list). We need to avoid duplication. Let's parse content.
Overview: first paragraph about AI at Capital One.
Team Description: description of IFX team.
Responsibilities: "In this role, you will:" followed by bullet-like sentences (partner..., design..., leverage..., invent..., contribute...). We'll put each as .
Ideal Candidate: list of qualities (love to build systems, passion..., adapt quickly..., love asking..., courage..., deeply technical..., resilient trail blazer...). Could be under Skills or Requirements? Probably Skills.
Basic Qualifications: bullet: Bachelor's degree ... plus at least 4 years experience ... or Master's plus 2 years. At least 4 years experience programming with Python, Go, Scala, or Java.
Preferred Qualifications: list of items.
We could have Requirements = Basic Qualifications, Qualifications = Preferred Qualifications, Skills = Ideal Candidate (or combine). But we need to follow headings: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule.
We'll include About the role (overview + team description). Responsibilities (the list). Requirements (Basic Qualifications). Qualifications (Preferred Qualifications). Skills (Ideal Candidate traits). Benefits (the benefits statement). Pay (salary ranges). No Schedule.
We must not repeat job title as heading. No Job ID etc.
We must preserve all substantive information; do not invent or summarize away detail. So we need to include all details from those sections.
Let's extract exact text.
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."
Responsibilities bullet list: after "In this role, you will:" we have:
- 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, 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, Nemo Guardrails, PyTorch, and more.
- Invent and introduce state-of-the-art LLM 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.
Ideal Candidate list: after "The Ideal Candidate:" we have sentences:
- 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 enable you to see and exploit optimization opportunities that others miss.
- You are a resilient trail blazer 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 4 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 2 years of experience developing AI and ML algorithms or technologiesAt least 4 years of experience programming with Python, Go, Scala, or Java"
Note there is a missing space before "At least". We'll keep as is.
Preferred Qualifications: list:
- 6 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 AI services
- Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, 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
- Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production
Also note: "Capital One will consider sponsoring a new qualified applicant for employment authorization for this position." That's a note about sponsorship; could be included maybe in About the role or Requirements? It's substantive. Where to place? Could be in About the role or maybe a separate note but we have no heading for sponsorship. Could add to About the role paragraph? Might be better to include in About the role as an extra sentence. But we must not invent headings. We could add a short paragraph after team description about sponsorship. Since it's substantive, we should preserve it. Where to put? Could be part of About the role (overview) or maybe a separate section like "Additional Information". But we only allowed headings list; we could add a
under About the role after the team description. That's fine. Also salary info: we need to include Pay section with the ranges. Benefits: we have statement about benefits. We must not include boilerplate like EEO, equal opportunity, scam warning, etc. So we will omit those paragraphs. Now construct HTML. Structure:
About the role
Overview paragraph...
Team Description paragraph...
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
Responsibilities
- ... ...
Requirements
- Bachelor'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, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies
- At least 4 years of experience programming with Python, Go, Scala, or Java
Qualifications
- 6 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 AI services
- Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, 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
- Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production
Skills
- 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 enable you to see and exploit optimization opportunities that others miss.
- You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown.
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.
Pay
The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.
- Cambridge, MA: $197,300 - $225,100 for Lead AI Engineer
- McLean, VA: $197,300 - $225,100 for Lead AI Engineer