Back
Mid-level, metro role with niche LLM/agent skillset yields moderate applicant competition.
Requires specialized LLM and agent production expertise, limiting cross-industry portability.
Explicit minimum experience plus mandatory LLM, agent frameworks, cloud, and MLOps skills.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Design, build, and deploy autonomous AI agent systems with multi-step workflows using large language models and tool orchestration frameworks.
Develop and implement agent reasoning loops, prompt engineering, orchestration workflows, and safety guardrails to ensure reliable and secure production-grade solutions.
Build evaluation, monitoring, and CI/CD frameworks for agent systems and integrate them with enterprise systems to automate business workflows.
Minimum 2 years AI engineering experience with at least 1 year in LLM or agent systems in production.
Proficiency in Python and experience with agent frameworks like LangChain, LangGraph, AutoGen, CrewAI, or Semantic Kernel.
Experience designing and testing tool integrations (REST APIs, vector DBs, SQL executors) and implementing safety controls against prompt injection and hallucination.
Familiarity with cloud platforms (AWS/GCP/Azure), containerization (Docker, Kubernetes), and MLOps/AIOps tooling (MLflow, Weights & Biases).
Experienced in designing complex agentic architectures (ReAct, plan-execute, reflection loops) with memory and caching layers for scalable production.
Skilled in prompt and context engineering, domain-specific LLM tuning (LoRA, PEFT, QLoRA, RLHF), and secure tool orchestration (Model Context Protocol).
Proficient in building comprehensive evaluation frameworks and continuous improvement feedback loops for autonomous AI agents.