Role OverviewDesign and ship production agent systems that automate KYB, underwriting, and risk decisions on regulated financial data. Partner closely with our Chief AI Officer, applied scientists, and platform teams.
What You Will Do
Design and ship multi-step agentic systems, architect agent graphs, build the retrieval layer, own the eval stack, expose agents to production systems, drive production MLOps, and mentor engineers.
Why It Might Be a Fit
5+ years of software engineering experience, with 2+ years building production LLM or agentic systems, hands-on experience with a modern agent framework, and strong RAG fundamentals.
Requirements
- 5+ years of software engineering experience
- 2+ years building production LLM or agentic systems
- Hands-on experience with a modern agent framework (LangGraph strongly preferred)
- Strong RAG fundamentals chunking, embeddings, hybrid retrieval, reranking, grounding
- Real eval experience golden sets, offline and online evaluations
- 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
- Health Care Plan (Medical, Dental & Vision)
- Retirement Plan (401k, IRA)
- Life Insurance
- Flexible Paid Time Off
- 9 paid Holidays
- Family Leave
- Free Food & Snacks (Orlando)
- Wellness Resources
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