LLM Engineer - 2
Posted Updated
Description
About the Role:
The Senior LLM Engineer will lead the design, development, and deployment of complex, autonomous agentic AI solutions within production environments, working across multi-agent frameworks and orchestrating large language models. The position is or scalable applied AI, with a focus on delivering robust and fair agentic systems that deliver organizational value, autonomy, and operational efficiency.
Responsibilities:
● Architect, design, and deploy scalable agentic AI systems that coordinate LLMs, multi-agent collaboration, and external tool integrations through advanced tool calling.
● Develop, maintain, and optimize AI-driven pipelines utilizing frameworks such as LangGraph, ADK and LangChain, enhancing data inference and orchestration.
● Integrate agentic AI solutions into enterprise workflows, automating complex business functions (e.g., customer service, supply chain, decision support).
● Proactively address system evaluation, debug AI agent workflows, and ensure compliance with emerging regulatory and ethical guidelines.
● Promote security, transparency, fairness, and reliability across all deployed agentic systems.
● Mentor junior engineers, contribute to cross-functional teams, and champion the adoption of state-of-the-art LLM technologies and practices.
Requirements
Requirements:
● At least 1 year of experience with LangGraph (must have)
● 4+ years of overall experience working on industry projects
● Experience with LangChain, and other agentic orchestration frameworks.
● Deep proficiency in designing and deploying multi-agent frameworks and sophisticated tool-calling or API orchestration pipelines.
● Design and implement continuous monitoring systems for autonomous AI agents, ensuring performance, reliability, adherence to ethical guardrails, and optimal cost/latency in production.
● Develop and execute scalable LLM evaluation methodologies (including code-based, LLM-as-a-Judge) to rigorously assess model quality, safety, and goal alignment.
● Proficiency in Python
● Familiarity with retrieval-augmented generation (RAG) and modern vector databases (Pinecone, Weaviate).
● Experience with cloud platforms (AWS, GCP, Azure), MLOps practices, and production-grade deployment.
● Strong understanding of data privacy, model security, and compliance with current AI regulations and frameworks.
Preferred Skills
● Experience with Hugging Face, Neo4j, or knowledge graphs.
● Background in autonomous decision-making systems, anomaly detection, and dynamic process optimization.
● Track record of publishing, presenting, or open-sourcing agentic AI innovations.
● Strong problem-solving aptitude, collaborative mindset, and excellent communication skills.