Tech Stack
AWSCloudDjangoPythonRayTerraform
About the role
- Architect and build the AI and automation backbone of the company
- Deploy, evaluate, and monitor ML/LLM systems in production
- Partner with product and operations to translate real customer pain points into intelligent, self-healing systems
- Build and lead a small technical team (5–10 engineers) as the platform scales over the next 24 months
- Own the end-to-end technical architecture: service orchestration, observability, and AI/ML pipelines
- Build, train, and deploy AI agents that automate IT workflows (troubleshooting, monitoring, patching, access management, etc.)
- Lead development of scalable backend systems (Python, Django/FastAPI, Pydantic, etc.) on AWS with EKS/Helm
- Recruit, mentor, and lead early technical hires across backend, MLOps, and automation domains
Requirements
- 5+ years of software engineering experience, including 2–3 years building or operating ML systems in production
- Expertise in Python and experience with backend frameworks (Django/FastAPI), MLOps tools (Ray, MLflow, W&B, etc.) and Agentic Frameworks (LangChain, LangGraph, PydanticAI, CrewAI, Autogen, etc.)
- Experience deploying models or agent systems on cloud infrastructure (AWS preferred; EKS/Helm/Terraform a plus)
- Familiarity with LLM orchestration or multi-agent frameworks
- Strong foundation in observability, logging, and production reliability
- Demonstrated ability to lead and scale small teams (5–10 engineers)
- Health insurance
- Retirement plans
- Paid time off
- Flexible work arrangements
- Professional development
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
PythonDjangoFastAPIMLOpsRayMLflowW&BLangChainLangGraphPydanticAI
Soft skills
leadershipmentoringteam buildingcommunicationproblem-solving