Python AI Engineer

We are hiring a **Python AI Engineer** to operate and evolve the infrastructure behind an enterprise knowledge base platform as it transitions from a Confluence-focused RAG chatbot into a broader, agentic knowledge system. Today, our platform supports Confluence/GitHub ingestion chunking pgvector RAG retrieval FastAPI serving. In our next growth phase, we are expanding toward hybrid retrieval (vector + sparse + graph), multi-source ingestion, robust evaluation pipelines, agent infrastructure, and shared chat platform primitives. If you are passionate about building scalable, reliable, and production-grade AI infrastructure rather than just chasing demo behavior, we want to hear from you. Req.#1093687315 *The recruiting efforts for this position are intended to fill an existing vacancy for a new position.* **Responsibilities** * Architect and implement robust backend services using Python 3.11, FastAPI, Pydantic, SQLAlchemy async, and asyncpg * Design trade-offs around retrieval quality, latency, cost, safety, and operational simplicity * Build production-grade agent runtime capabilities, including memory boundaries, tool sandboxing, permissions, and budget controls * Improve answer grounding, failure analysis, and citation enforcement for enterprise-grade dependability * Create comprehensive observability and operational feedback loops using OpenTelemetry, Prometheus/Grafana, Docker/Helm, and GitHub Actions * Ingestion infrastructure across current and future content sources * Full-stack observability across application, pipeline, database, and model-serving behavior * Cost, latency, throughput, and failure-mode management for AI-heavy workloads * Release workflows that validate AI behavior changes, not just code compilation * Partner closely with product and engineering teams to support multiple conversational surfaces through a unified knowledge platform **Requirements** * Strong, hands-on Python experience in platform, automation, or infrastructure-heavy environments * Experience building CLI tools using Python, Golang, or Rust * Hands-on experience with LangGraph, LangChain, pgvector, and modern retrieval pipelines * Experience designing evaluation frameworks for LLM-backed systems, including regression detection and quality measurement * Strong experience with Docker, Helm, GitHub Actions, and Kubernetes-oriented workflows * Systems Understanding: Familiarity with the operational characteristics of embedding pipelines, vector search, and LLM-backed systems * Strong skills across metrics, tracing, dashboards, alerting, and log analysis * Experience with ingestion, ETL, or content-processing pipelines at scale * An innate ability to think in terms of reliability, cost, latency, throughput, and disaster recovery **Nice to have** * Experience with Qdrant, Neo4j, or other vector/graph infrastructure * Prior experience supporting RAG, search, evaluation, or agent platforms * Background in enterprise or highly regulated environments * Fam