Python Automation Engineer (AI-Driven)

Quick Facts

• Role: Python Automation Engineer (AI-Driven)

• Focus: Shared AI augmentation platform layer and production engineering

• Work mode: Remote with significant overlap with US Eastern Time zone

Description

You will build and own the shared Python library and services that every AI augmentation solution uses for authentication, configuration, logging, request context, and safe access to models. You will also define engineering standards and platform templates so new solutions move from first commit to first production deployment quickly. The role involves hands-on work with AI coding agents, production readiness assessments, mentoring, and shipping via AWS EKS and GitLab CI.

Responsibilities

• Build and maintain the shared Python library for authentication, configuration, logging, and request context; migrate existing solutions onto it.

• Create the project template for new solutions to reach production rapidly.

• Design shared services starting with an AI gateway (model access, per-solution cost tracking, and audit log) with de-identification through approved services.

• Run measured bake-offs to choose model/framework/library options and document decisions with evidence and fallbacks.

• Own and improve internal platform components (AI coding agent skills marketplace, architecture/assessment tool, AI tools portal, demo hub).

• Ship and manage releases on AWS EKS via GitLab CI (pipelines, versioned releases, configuration/secrets, and fail-closed gates).

• Assess solutions for production readiness (security, reliability, testing) and create remediation plans with owners and dates.

• Mentor platform developers; write docs and agent skills so work can be picked up without you.

Requirements

• 10+ years building and running production software; several years setting technical direction for other engineers.

• Strong Python, including FastAPI and packaged libraries used by other teams; working knowledge of Node.js and TypeScript.

• Daily hands-on experience using AI coding agents to ship production code with a clear process to detect and verify failures.

• Production experience with LLM APIs including prompt/output design, evaluation on real tasks, cost/latency tradeoffs, and fallback when models are unavailable or unapproved.

• AWS, Kubernetes (EKS), containers, and CI/CD pipelines you have written (ideally GitLab CI).

• Authentication/authorization in practice: OIDC and OAuth2 with an identity provider such as Okta, least privilege, and secrets kept out of code/logs/chat.

• Testing discipline: browser tests (Playwright or similar) against a real server, plus unit/integration tests, enforced by CI gates.

• Clear written decision records and status reporting for executive audiences.

• Exceptional verbal and written English communication.

• Comfort working later hours to support collaboration with US Eastern time.

Benefits

• B2B contract opportunity with 40 hours/week.

• Remote role with real-time collaboration overlap with the US Eastern Time zone.

• Opportunity to shape the shared platform used by multiple production AI solutions.