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

Work arrangement
Yes