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Senior Agentic, AI Engineer
Worth AISenior Agentic AI Engineer at Worth AI designing and shipping production agent systems that automate KYB, underwriting, and risk decisions. Collaborate with AI officers and engineers on advanced AI projects.
Tech Stack
Tools & technologiesAWSJavaScriptNode.jsPythonTerraformTypeScript
About the role
Key responsibilities & impact- Design and ship multi-step agentic systems (planner/executor, tool-using, multi-agent, human-in-the-loop) for onboarding, underwriting, case review, and continuous monitoring.
- Architect agent graphs in LangGraph (or comparable — CrewAI, AutoGen, Claude Agent SDK) with explicit state, durable execution, retries, and safe fallbacks.
- Build the retrieval layer powering our agents — chunking, hybrid search, reranking, and grounded citation.
- Own the eval stack: golden sets, offline regression suites, LLM-as-judge, online A/B and shadow evals, and red-teaming for jailbreaks, prompt injection, and PII leakage.
- Expose agents to production systems via well-typed tools and MCP servers. Treat tool surface area as a product.
- Drive production MLOps: deployment, versioning, traffic shaping, cost/latency budgets, tracing, and on-call playbooks for agent incidents.
- Partner with security and compliance to keep agents inside SOC 2, GDPR, CCPA, and fair-lending posture — auditability and explainability built in, not bolted on.
- Mentor engineers on agent patterns, prompt hygiene, eval discipline, and LLM failure modes.
Requirements
What you’ll need- 5+ years of software engineering experience, with 2+ years building production LLM or agentic systems (not just notebooks or demos).
- Hands-on experience with a modern agent framework (LangGraph strongly preferred) and a track record of shipping agents that run, fail gracefully, and recover.
- Strong RAG fundamentals chunking, embeddings, hybrid retrieval, reranking, grounding — and judgment about when RAG isn’t the right answer.
- Real eval experience golden sets, offline and online evaluations, used to make ship/no-ship calls.
- Production MLOps fluency: deployed LLM workloads under real latency, cost, and reliability constraints.
- Strong Python; comfortable in TypeScript / Node.js.
- Solid systems engineering instincts APIs, async patterns, queues, databases, distributed system failure modes.
- Calibrated communicator; thrives in ambiguous, fast-moving environments.
- Prior experience in fintech, lending, payments, KYB/KYC, fraud, or AML.
- Experience building MCP servers or other structured tool interfaces for LLMs.
- Background in classical ML (ranking, scoring, calibration).
- Experience designing explainable / auditable AI workflows for regulated environments.
- Open-source contributions to agent frameworks, eval tooling, or retrieval libraries.
- AWS depth (EKS, MSK, RDS, S3, Lambda) and IaC with Terraform.
Benefits
Comp & perks- Health Care Plan (Medical, Dental & Vision)
- Retirement Plan (401k, IRA)
- Life Insurance
- Flexible Paid Time Off
- 9 paid Holidays
- Family Leave
- Remote
- Hybrid work (for Orlando Associates)
- Free Food & Snacks (Orlando)
- Wellness Resources
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
software engineeringproduction LLM systemsagent frameworkschunkinghybrid retrievalrerankingMLOpsPythonTypeScriptsystems engineering
Soft Skills
calibrated communicatormentoringthrives in ambiguity