Senior LLM Engineer

Role Overview

The Senior Agentic AI 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 for scalable applied AI, with a focus on delivering robust and fair agentic systems that deliver organizational value, autonomy, and operational efficiency.​

Key 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.​

Required Qualifications

• 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.​