Senior Python AI Engineer - Only W2

Role: Senior Python AI Engineer Location: Remote (US) Job Type: W2 Contract Experience Required: 10+ years Jd

• Knowledge Base Infrastructure

We are hiring a Python Platform Engineer to operate and evolve the infrastructure behind an enterprise knowledge base platform that is moving from a Confluence-focused RAG chatbot into a broader agentic knowledge system . Today, the platform supports Confluence/GitHub ingestion chunking pgvector RAG retrieval FastAPI serving . Over the next phase, we are expanding toward hybrid retrieval (vector + sparse + graph), multi-source ingestion, evaluation pipelines, agent infrastructure, harness and shared chat platform primitives.

What You'll Own

• Architect and implement backend services in Python 3.11, FastAPI, Pydantic, SQLAlchemy async, and asyncpg
• Design retrieval and orchestration trade-offs around quality, latency, cost, safety, and operational simplicity
• Build production-grade agent runtime capabilities: memory boundaries, tool sandboxing, permissions, and budget controls
• Improve answer grounding, failure analysis, and citation enforcement rather than optimizing for demo behavior
• Create observability and operational feedback loops with OpenTelemetry, Prometheus/Grafana, Docker/Helm, and GitHub Actions
• Work closely with product and engineering partners to support multiple conversational surfaces through one knowledge platform
• Ingestion infrastructure across current and future content sources
• 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

Qualifications

• Strong hands-on experience with Python 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
• Familiarity with the operational characteristics of embedding pipelines, vector search, and LLM-backed systems
• Strong observability skills across metrics, tracing, dashboards, alerting, and log analysis
• Experience with ingestion, ETL, or content-processing pipelines at scale
• Ability to think in terms of reliability, cost, latency, throughput, and recovery

Nice To Have

• Experience with Qdrant, Neo4j, or other vector/graph infrastructure
• Experience supporting RAG, search, evaluation, or agent platforms
• Experience in enterprise or regulated environments
• Familiarity with Vault, Splunk, Artifactory, ECR
• Comfort using AI-assisted engineering workflows in day-to-day work