Agentic AI Engineer
Spotted 3h agofulltime
Job description
About this role
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Agentic AI Engineer
Location: Burlingame, CA – Hybrid
Job Type: Full-Time
Experience: 7–10 Years
About the Role
We are looking for an experienced Agentic AI Engineer to build and support production-ready AI systems, LLM infrastructure, and autonomous AI agents.
The ideal candidate will have a strong Software/Backend Engineering background and have transitioned into Generative AI / Agentic AI development.
You will work closely with AI and engineering teams to build scalable, reliable, and high-performance AI platforms.
Key Responsibilities
- Build and deploy LLM and Generative AI applications in production.
- Develop and scale AI agents and multi-agent workflows.
- Work with frameworks such as LangChain, LangGraph, and CrewAI.
- Build and optimize LLM serving and inference using tools such as vLLM, Triton, or Ray Serve.
- Manage AI workloads using Kubernetes, Docker, and cloud platforms.
- Build RAG pipelines, memory systems, and integrations with vector databases.
- Implement monitoring, logging, tracing, and evaluation for AI/LLM applications.
- Develop CI/CD pipelines and internal tools for deploying AI models and agents.
- Troubleshoot performance, scalability, GPU, and production issues.
Required Skills
- 7–10 years of software, backend, ML, or infrastructure engineering experience.
- Strong Python programming skills.
- Strong background in Software/Backend Engineering.
- Experience with LLMs / Generative AI / Agentic AI.
- Hands-on experience with LangChain, LangGraph, or CrewAI.
- Experience with Kubernetes and Docker.
- Experience with AWS, GCP, or Azure.
- Experience with LLM serving tools such as vLLM, Triton, or Ray Serve.
- Strong understanding of distributed systems and scalable infrastructure.
Preferred Skills
- Vector databases: Pinecone, Milvus, or Qdrant
- RAG and AI memory systems
- GPU/TPU infrastructure
- Terraform or Pulumi
- Go or Rust
- LLMOps / AgentOps
- Model optimization, quantization, LoRA, or KV caching
- AI observability tools such as Langfuse, Arize, or Datadog
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