7-10 years of software / AI engineering experience, with a strong track record of shipping systems
to production.
Python: Expert-level Python clean, well-tested, production-quality code and robust grasp of software
design.
Agent building: Hands-on experience building LLM/GenAI agents: agent frameworks (e.g., Lang Chain,
Lang Graph, CrewAI, or similar), tool/function calling, RAG, and prompt engineering.
YAML: Proficiency with YAML for configuration, workflow definition, and infrastructure/deployment
tooling.
LLMs: Experience with LLM APIs and models (e.g., Anthropic Claude, OpenAI, open-source models) and
understanding of their trade-offs.
Rigor: Solid understanding of evaluation, observability, and safety/guardrails for agentic systems.
Cloud & infra: Familiarity with cloud platforms (AWS/Azure/GCP), containers, and CI/CD.
Nice to Have
Domain: Experience in data security, cybersecurity, or data management domains.
OSS: Contributions to open-source agent or ML tooling.
Retrieval: Experience with vector databases, embeddings, and retrieval systems.
Scale: Background in MLOps or distributed systems.