Job description
Project Role : Large Language Model Architect
Project Role Description : Architect large language models (LLM) that can process and generate natural language. Design neural network parameters, trained on large quantities of unlabeled text data.
Must have skills : Machine Learning (ML)
Good to have skills : NA
Minimum 7.5 year(s) of experience is required
Educational Qualification : 15 years full time education
Summary:
Design and guide implementation of production-grade agentic AI solutions, with hands-on ownership of critical architectural components and integration patterns.
Hands-on proficiency building reference implementations with LangGraph, OpenAI Agents SDK, Google ADK, PydanticAI or CrewAI, and using Cursor, Claude Code or Codex to accelerate coding while retaining control over orchestration, state, testing and failure recovery.
Must have personally designed and implemented major components of AI systems that reached production. Prototype-only experience does not meet the requirement.
Roles & Responsibilities:
- Design agent workflows, orchestration, tool use, memory, retrieval, and human-in-the-loop patterns.
- Translate business requirements into scalable technical designs.
- Build reference implementations and validate architecture through working code.
- Integrate agents with enterprise APIs, databases, workflow systems, and identity platforms.
- Define evaluation, tracing, guardrails, recovery, and operational monitoring.
- Review code and designs, resolve technical risks, and mentor engineers.
- Support production readiness, performance tuning, and incident resolution.
Professional & Technical Skills:
- Hands-on Python and modern agentic or GenAI frameworks.
- RAG, vector and graph retrieval, prompt and context engineering, and structured outputs.
- Microservices, APIs, queues, containers, cloud deployment, and CI/CD.
- Security, observability, model evaluation, latency, and cost controls.
This job post has been translated by AI and may contain minor differences or errors.
