Python AI Engineer - Agentic AI

Since launching in March, the team has successfully built 6 AI agents and is now entering the next phase of scaling and enhancement. The first production agents are scheduled to go live on August 24th. Long-term roadmap is expected to expand to 20+ AI agents. This is one of the bank’s first major Agentic AI initiatives and is considered a highly visible, strategic program., Resources will primarily be building, enhancing, and supporting AI agents rather than spending significant time in meetings. Daily collaboration occurs through team standups and close interaction with developers and architects. Candidates should be comfortable communicating technical needs and blockers, though executive-facing responsibilities are minimal., * Purchase any product, service, or gift cards from us or for us as part of an application, interview, or selection process.

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Strong backend Python developer with experience building and supporting microservices-based applications. Experience designing and consuming APIs. Familiarity with Large Language Models (LLMs), Agentic AI frameworks, and AI orchestration concepts. Experience working with MongoDB and vector databases. Financial services experience is not required., Python: 5+ years Microservices: 5+ years API Development/Integration: 5+ years MongoDB: 5+ years Agentic AI: 2+ years preferred, Python software engineering REST API development Microservices architecture Distributed systems design Backend service development FastAPI AsyncIO Multiprocessing Performance tuning and profiling Caching strategies Database/query optimization Event-driven architecture High-availability and fault-tolerant system design

Generative AI / LLM Skills Generative AI application development Large Language Models Agentic AI systems Multi-agent workflow design Retrieval-Augmented Generation Hybrid RAG architectures Knowledge graph-enhanced RAG Prompt engineering Prompt orchestration Tool calling LLM routing and fallback strategies Fine-tuning evaluation Model evaluation frameworks Hallucination detection Human-in-the-loop validation Text-to-SQL using LLMs Schema-aware prompting Embeddings and semantic search

AI Platform & Architecture Skills Enterprise AI platform architecture Scalable AI workflow design AI governance standards AI guardrails implementation Responsible AI controls PII redaction Audit logging Model usage monitoring Latency, cost, and accuracy optimization AI/ML feature engineering Recommendation systems Feedback loops for model improvement

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