LLM Engineer - 2

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 Lang. Graph, ADK and Lang. Chain, 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

● At least 1 year of experience with Lang. Graph (must have) ● 4+ years of overall experience working on industry projects ● Experience with Lang. Chain, 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.