Agentic AI Engineer
Tasks
- Apply security and governance controls
- Build CI CD pipelines for agent workflows
- Build evaluation frameworks for LLMs and agents
- Build multi agent systems with tool use
- Design Agentic AI systems
- Develop prompt and context engineering strategies
- Ensure observability with tracing and monitoring
- Establish feedback loops for continuous improvement
- Fine tune LLMs for domain specific applications
- Implement Model Context Protocol integrations
- Implement reasoning loops with safety guardrails
- Implement retrieval and grounding with vector databases
- Integrate agents with enterprise APIs
- Optimize agents for latency cost and scalability
- Orchestrate agent workflows and task routing
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | Access Control | Autogen | Azure | CI/CD | CrewAI | Docker | Embeddings | FastAPI | GCP | Injection Defense | Instruction Tuning | Knowledge graphs | Kubernetes | LLM Evaluation | LLM-as-judge | Langchain | Langgraph | Language Models | Large Language Models | LoRA | MLOps | MLflow | Model Context Protocol | PEFT | Prompt engineering | Prompt injection | Prompt injection defense | Python | QLoRA | REST APIs | RLHF | Ragas | React | Retrieval-Augmented Generation | SQL | Semantic Kernel | Structured Output | Vector Databases | Weights and Biases
Education
N/A
Roles
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