AI Engineer 5 (AI Foundations)
$230k - $262k • San Jose, CA • Full-time
Posted 12d ago
About the job
Capital One is building responsible and reliable AI systems to transform banking. We are at the forefront of enterprises leveraging AI, using machine learning to create personalized customer experiences and bring humanity and simplicity to banking. Our Intelligent Foundations and Experiences (IFX) team is central to this vision, building and deploying proprietary AI solutions that deliver value to millions of customers. You will partner with cross-functional teams to deliver AI-powered products, design, develop, test, deploy, and support AI software components, and leverage a broad stack of Open Source and SaaS AI technologies. You will invent and introduce state-of-the-art foundation model optimization techniques to improve the performance of large-scale production AI systems and contribute to the technical vision and roadmap of foundational AI systems.
Responsibilities
- Partner with cross-functional teams to deliver AI-powered products.
- Design, develop, test, deploy, and support AI software components including foundation model training, LLM inference, agents, similarity search, guardrails, model evaluation, experimentation, governance, and observability.
- Leverage Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, and PyTorch.
- Invent and introduce state-of-the-art foundation model optimization techniques to improve performance (scalability, cost, latency, throughput) of large-scale production AI systems.
- Contribute to the technical vision and long-term roadmap of foundational AI systems.
- Design, implement, and optimize multi-model orchestration pipelines integrating LLMs, vector search, and domain-specific models.
- 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 AI engineers, fostering cross-domain learning and elevating organizational technical maturity.
Requirements
- 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.
- Experience leading development of 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 applying 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.