Associate Manager - AI/ML Engineering

IDC's Data COE is seeking an Associate Manager, AI/ML Engineering to design, build, and productionize agentic AI workflows that automate and scale IDC's data operations and analytics products. This role sits at the center of IDC's shift from static data pipelines to autonomous, tool-using AI agents multi-step systems that plan, call tools, retrieve and reason over IDC's proprietary data assets, and operate under human-reviewed guardrails in production.You will build agent loops with tool calling, orchestration, and memory/state management, design evaluation harnesses that measure agent accuracy, latency, and cost; and implement retrieval-augmented generation (RAG) against IDC's intelligence assets so agent outputs stay grounded in verified data. This is a hands-on technical role for someone who has actually shipped agentic AI systems to production, not just experimented with them.This is an exciting opportunity to help define how IDC builds, evaluates, and governs agentic AI directly supporting the Data COE's broader strategy of transformation work with reliable, monitored AI agents.What You’ll Do

• Design, build, and productionize agentic AI workflows multi-step agent loops with tool calling, sub-agent orchestration, and memory/state management using frameworks such as LangGraph, the Model Context Protocol (MCP), and the Claude Agent SDK/Claude Code.
• Develop evaluation harnesses and observability for deployed agents, measuring accuracy, latency, and cost, and diagnosing failure modes such as hallucination, drift, prompt injection, and cost runaway before and after release.
• Implement retrieval-augmented generation (RAG) and semantic search against IDC's proprietary data assets so agent outputs stay grounded in verified data.
• Define guardrails, escalation points, and human-in-the-loop review boundaries for agentic systems operating on production data.
• Partner with Data COE leadership to translate business requirements including IDC's agentic data-collection and Tracker-automation strategy into agent specifications and delivery plans.
• Own model/prompt-pipeline versioning for deployed agents, including production incident response and continuous improvement.
• Guide and review the work of junior engineers contributing to agentic workflow projects, and stay current on the fast-moving agentic AI tooling landscape.

• Bachelor's degree in Computer Science, Data Science, Engineering, or a related quantitative field.
• 5+ years of experience in data science or AI/ML engineering, including at least 2 years hands-on building and shipping agentic AI or LLM applications in production.
• Hands-on experience with machine learning, agent orchestration framework Claude Code/Claude Agent SDK and tool-calling / MCP-based integration patterns.
• Strong applied Python, SQL, and Snowflake fundamentals enough to assess solution feasibility and challenge technical proposals.
• Experience designing evaluation frameworks for agent accuracy, latency, and cost efficiency.
• Working understanding of agentic-system failure modes (hallucination, drift, prompt injection, cost runaway) and how to mitigate them through guardrails and human-in-the-loop review.
• People management experience comfortable directing and reviewing the work of junior team members alongside their own responsibilities.
• Travel: minimal (up to 10%).
• Work model: Hybrid (Czech Republic).

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