Hiring: GenAI Engineering Lead Company: Bessemer Trust Location: Woodbridge, NJ Job Posted Time: 2026-09-10 11:00:07 Employment Type: Remote Target Skills & Keywords : API Gateway, AWS, CI/CD, Fine-tuning, IAM, LLM, Lambda, Python, RAG, REST, Wealth Management About the job Experience: •10+ years in software engineering, including 2+ building LLM-powered systems, including time as technical lead for a small team — setting direction, reviewing designs and code, and still writing code yourself. •119 years, Bessemer Trust has operated continuously in a single line of business, independently owned by one family. Required Skills: •Design and build agentic systems end to end — orchestration, tool and API integration, memory, retrieval, and human-in-the-loop patterns — and stay hands-on in the codebase. •Lead a team of developers: set technical direction, review designs and code, and mentor engineers. •Own the agent framework stack (LangGraph, Strands, Bedrock AgentCore, and what comes next) and the research behind it — evaluate what's emerging, prototype what looks promising, and make calls today that still hold up in six months. •Design the context layer our agents reason over — knowledge graphs, vector stores, and retrieval strategy — owning the data modeling, schema, and embedding decisions behind it. •Design and own the caching layer — semantic, prompt, and context caching with invalidation rules that keep results trustworthy — and drive latency and cost through model routing and right-sizing. •Own quality and safety: eval harnesses, regression suites, and observability for non-deterministic systems, plus guardrails, tool permissioning, PII handling, and human approval paths for high-impact actions. •Partner with business stakeholders to turn real problems into agent designs, work with platform and DevOps to deploy them securely, and leave behind the docs and reference patterns other teams build from. Qualifications: •Strong Python and modern engineering practice: testing, CI/CD, code review, observability, and iterative delivery. •Production experience with LLM-powered systems — breaking domain tasks down into reusable agents, tools, and skills, and shipping agentic workflows and RAG pipelines to real users rather than demos. •Depth in the retrieval and context layer: embeddings (including fine-tuned or domain-adapted models), vector search, chunking, and the data modeling and enrichment that determine retrieval quality — plus working knowledge of graph or other structured context stores and of caching strategies for latency and cost. •Hands-on with at least one agent framework or runtime (LangGraph, Strands, Bedrock AgentCore, or similar), with MCP or an equivalent tool-integration protocol, and a solid AWS foundation — Lambda, API Gateway, IAM, and Bedrock or equivalent model serving. •A research habit: able to evaluate an emerging model, framework, or pattern quickly, form a defensible opinion, and explain it to stakeholders. •Running vector or graph stores in production — sizing, index tuning, re-embedding and reindexing, backups, and access control — and building GraphRAG or hybrid retrieval on top of them. •Tuning a semantic cache in production — setting similarity thresholds, measuring hit rate against false-hit rate, and handling invalidation as underlying data changes. •AWS Bedrock, AgentCore, or a comparable enterprise GenAI platform. •Fine-tuning, distilling, or otherwise adapting models for specific tasks, and serving self-hosted or in-house models in production. •Work in a specialized domain where correctness matters — legal, financial, or regulatory — including delivery in security-sensitive environments. Compensation: •$200,000 - $240,000 / year •Flexible work environment (work from home / hybrid options) Interested candidates, please apply directly through the job posting on company's career page or try via AI auto apply on this platform. Don't miss this opportunity to join a forward-thinking team!