Senior AI Engineer

AI Engineer

Location:

San Francisco, CA

We are seeking a Senior AI Engineer with deep, hands‑on expertise in Generative AI, multi‑agent orchestration, and LLM‑based systems with Python to design, build, and scale secure, production‑grade AI platforms. The role requires strong engineering rigor, practical experience beyond PoCs, and the ability to operationalize agentic AI in complex enterprise environments.

• Generative AI & LLM Engineering
  • Strong hands‑on experience building LLM‑powered applications for reasoning, summarization, Q&A, and content generation.
  • Expertise in prompt engineering, prompt optimization, and systematic prompt evaluation.
  • Ability to generate structured and deterministic outputs for downstream consumption.
  • Apply grounding, response validation, and hallucination mitigation techniques.
• Multi Agent Orchestration & Lang Graph (Must Have)
  • Strong hands‑on experience designing and implementing multi‑agent AI systems.
  • Practical experience working with agent orchestration frameworks, specifically Lang Graph.
  • Design and implement orchestrator / supervisor agent patterns, intent routing, task decomposition, agent sequencing, dependency management and handoffs.
  • Implement tool‑calling patterns, shared context management, and output aggregation across agents.
  • Experience managing agent state, memory, and execution flow in production environments.
• Retrieval Augmented Generation (RAG)
  • Build and optimize RAG pipelines across large unstructured datasets.
  • Hands‑on experience with embedding strategies, vector databases and semantic search, chunking, ranking, and metadata‑based retrieval.
  • Ensure responses are traceable, explainable, and source grounded.
• AI Application Engineering
  • Strong backend engineering skills using Python.
  • Design modular, API‑first AI services using scalable architectures.
  • Integrate AI services with external systems and tools via secure APIs.
  • Efficient handling of long‑running agent workflows and asynchronous execution.
• Cloud Native AI & Platform Skills
  • Experience deploying AI solutions on cloud‑native platforms.
  • Familiarity with containerized AI workloads, CI/CD pipelines for AI and agent services, scalable fault‑tolerant system design.
  • Experience managing structured and unstructured data storage for AI workloads.
• AI Governance, Security & Reliability
  • Implement guardrails and safety controls, including prompt‑injection prevention, access control, role‑based execution, output validation, and policy enforcement.
  • Support observability for agent behavior and execution flow, confidence scoring, failure detection, usage patterns, and anomaly detection.
  • Design AI systems that are auditable, explainable, and enterprise ready.
• Collaboration & Technical Leadership
  • Provide technical leadership across AI and GenAI initiatives.
  • Review AI designs, orchestration flows, and implementation quality.
  • Mentor junior AI engineers on agent design and best practices.
  • Collaborate with architects, data scientists, and platform engineers.

• Strong experience as a Senior AI / GenAI Engineer.
• Proven, hands‑on experience with multi‑agent orchestration using Lang Graph.
• Advanced knowledge of LLMs and agentic AI systems, RAG architectures, and Python‑based AI development.
• Experience delivering production‑grade AI systems, not just experiments.

• Experience designing large‑scale agent‑based platforms.
• Exposure to LLMOps / MLOps practices.
• Familiarity with model and agent evaluation techniques.
• Experience working in regulated or security‑sensitive environments.

• Deliver scalable, reliable, and well‑orchestrated AI systems.
• Demonstrate deep hands‑on ownership of multi‑agent execution logic.
• Balance innovation with robustness, security, and maintainability.