Senior Agentic, AI Engineer

🕒 May 15

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Logo of Worth AI

Worth AI

11 - 50 employees

🤖 Artificial Intelligence

💳 Fintech

🏦 Banking

Artificial Intelligence • Fintech • Banking

Worth AI is a company that specializes in enhancing financial security and risk management through advanced AI-driven solutions. Their platform offers a suite of tools designed for seamless onboarding, compliance, and credit risk assessment. They help banks, fintech companies, and credit unions streamline operations by automating processes such as KYC/KYB compliance, reputation monitoring, and automated credit underwriting. Worth AI's technology provides real-time risk monitoring, predictive analytics, and AI-generated insights to improve decision-making, safeguard institutions, and boost revenue. Key offerings include Worth Score™, an AI-driven credit score solution, and unique AI underwriting systems that enhance the accuracy and efficiency of financial assessments.

📋 Description

• 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

• 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

• 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

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