Senior Python AI Engineer

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, PrometheGrafana, 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.