Lead AI Engineer

Job Description

GlobalLogic is building AI-first enterprise solutions that help global clients transform their digital platforms and products. As an AI Engineer, you’ll own the development of the core agentic frameworks, evaluation pipelines, and observability tooling that let it operate with safety, trust, and intelligence at scale. You won’t just be integrating AI into a product, you’ll be building the engineering systems that make it trustworthy.

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Requirements

Who You Are

• 5+ years of software engineering experience, including hands-on experience shipping agentic or LLM-backed systems that are used in production.

What You’ll Bring

• AI DLC experience: Demonstrated experience with AI Development Life Cycle practices and methodology.
• Orchestration: Production, hands-on experience with an agentic framework such as LangGraph, plus familiarity with MCP-based tool orchestration. Exposure to AutoGen, LlamaIndex, or CrewAI is a plus.
• Production Python engineering: Clean, modular, testable, maintainable code – you care about system reliability as much as model output.
• Evaluation & observability: Practical experience instrumenting tracing (LangSmith, Arize) and building CI/CD pipelines built specifically for LLMs.
• Engineering foundations: Distributed systems, scalable data pipelines (Kafka, SQL), and cloud-native infrastructure.
• Cloud-native deployment: Deep familiarity with shipping agentic workloads into production environments, ideally leveraging Kubernetes for enterprise scale.

Job Responsibilities

What You’ll Do

• Architect agentic systems: Design and implement multi-agent architectures that the rest of the team builds on top of.
• Practice eval-driven development: Build and own the evaluation harnesses that measure accuracy, hallucination, and performance before anything ships.
• Solve performance at scale: Tackle RAG latency optimization, context-window management, and intelligent information routing under real production load.
• Build observability: Ship tooling that gives the team real-time insight into model behavior and guardrail compliance.

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