AI Engineer 3 (AI Foundations)
$162k - $185k • McLean, VA • Full-time
Posted 1mo ago
About the job
Capital One is seeking an AI Engineer to join the Intelligent Foundations and Experiences (IFX) team, which is central to bringing the company's AI vision to life. This role involves partnering with cross-functional teams to build and deploy proprietary AI solutions that enhance customer experiences and business operations. The IFX team advances the state of the art in AI engineering and builds platforms that empower other teams across Capital One to leverage AI responsibly and at scale. You will contribute to reimagining how Capital One serves its customers and businesses through the transformative power of emerging AI capabilities.
Responsibilities
- Partner with engineers, research scientists, and product managers 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, and governance.
- 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 AI systems.
- Contribute to the technical vision and long-term roadmap of foundational AI systems.
- Lead development and benchmarking of multi-turn conversational and tool-using agent workflows, ensuring performance and safety metrics.
- Implement scalable pipelines for training, fine-tuning, and deploying foundation or domain-specific models.
- Collaborate with research and data engineering teams to curate datasets and improve model evaluation methodologies.
- Contribute to governance and security efforts for model traceability, lineage documentation, and version control.
- Mentor junior AI engineers and advocate for engineering excellence, reproducibility, and responsible experimentation.
Requirements
- Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 3 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 1 year of experience developing AI and ML algorithms or technologies.
- At least 3 years of experience programming with Python, Go, Scala, CUDA, or Java.
- Experience contributing to development of AI system components with tradeoff decisions around cost, latency, throughput, and accuracy.
- 4 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud).
- Experience 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, 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.
- Demonstrated ability to evaluate and optimize LLM performance using quantitative metrics (accuracy, coherence, latency, cost).
- Hands-on experience implementing retrieval-augmented generation (RAG), vector database integrations, and fine-tuning workflows.
- Experience applying prompt-engineering strategies, safety guardrails, and red-teaming methodologies to production AI systems.