Agentic AI Engineer, Staff
Indexed description
Energy feeds on energy. If you flourish in a fast paced, results-oriented environment, if you want to achieve individual success within a “team first” organization, and if you believe you can contribute and succeed in a demanding yet collegial atmosphere, then Lattice may well be just what you’re looking for.
Responsibilities & Skills
We are looking for a Staff-level engineer to join our Agentic AI team to build the next generation of EDA automation products. This role focuses on designing, orchestrating, and scaling agentic systems.
You will design and develop multi-agent workflows, build retrieval and knowledge systems, design guardrails and error-recovery loops, and ensure reliability, traceability, and safe execution in production.
This role is ideal for someone with hands-on experience shipping agentic AI systems, LLM-driven workflows, or automation engines at scale.
Key Responsibilities
- Implement and optimize multi-agent frameworks (LangGraph, LlamaIndex agents, AutoGen, CrewAI).
- Define agent interfaces, policies, and error‑handling/repair strategies.
- Implement strict schema‑bound LLM calls (JSON, XML, structured tool commands).
- Implement constrained decoding, schema-bound generation, and deterministic reasoning passes.
- Build document ingestion pipelines with chunking, metadata tagging, and embeddings.
- Build domain‑aware RAG systems with citation‑based referencing.
- Develop multi layer guardrails using schema validation, rule based checks, and policy engines.
- Implement self critique, repair loops, and fallback strategies for model outputs.
- Build model serving pipelines (vLLM/TGI/Triton), caching, batching, and streaming.
- Implement logging, tracing, observability, and offline evaluation pipelines.
- 7+ years’ experience in developing large web based applications with 1+ years building LLM-powered tools
- Strong experience in backend or distributed system design (gRPC/REST, microservices, queues).
- Experience building workflow engines or automation systems (Airflow, Temporal, Dagster)
- Expertise in Python, PyTorch, and modern AI frameworks (HuggingFace, vLLM, LangChain).
- Developing software with frameworks like Cursor, Copilot
- Experience building robust RAG pipelines (embedding optimization, retrieval metrics).
- Experience designing structured model interactions (JSON schema, function‑calling, tool‑use).
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