Scrum Master – AI / GenAI Pods

Location: Chicago, IL (Local)
Experience: 10+
VISA: TN, L2, (No H1B & OPT)


Job Overview

We are seeking an experienced Scrum Master to guide and enable multi-disciplinary AI Pods (comprising Data Scientists, ML Engineers, Prompt Engineers, Data Engineers, and Software Developers). In this role, you will facilitate Agile practices tailored to the non-linear, experimental nature of AI/ML software development. You will manage cross-functional dependencies, help the team navigate research unpredictability, and ensure the seamless delivery of enterprise-grade AI products into production.

Key Responsibilities

·         Agile Facilitation: Lead core Scrum ceremonies (Sprint Planning, Daily Stand-ups, Backlog Refinement, Sprint Reviews, and Retrospectives) adapted specifically for AI model development and software integration cycles.

·         AI Pod Operations: Help the team balance exploratory research (spikes, model training, prompt iteration) with predictable engineering deliverables (API integrations, UI deployment).

·         Dependency & Risk Management: Manage complex cross-pod dependencies across data platform teams, cloud infrastructure, AI governance/ethics boards, and business stakeholders.

·         Impediment Removal: Proactively remove blockers related to data pipelines, GPU compute availability, API limits, model validation delays, and cross-team alignment.

·         Stakeholder Alignment & Metrics: Translate AI uncertainty (e.g., accuracy tradeoffs, latency constraints) into business terms for product managers and leaders. Track velocity, cycle times, model deployment cadence, and sprint health.

·         Continuous Improvement: Foster an experimental mindset, encourage continuous learning, and refine agile practices based on retrospective feedback.

Key Requirements & Qualifications

·         4+ years of Scrum Master experience, with at least 1–2 years embedded within AI, ML, Data Science, or GenAI engineering teams.

·         Certified ScrumMaster (CSM), Advanced CSM (A-CSM), PSM II, or SAFe Scrum Master certified.
Solid conceptual understanding of the AI/ML lifecycle (Data Collection  Feature Engineering  Model Training  Fine-Tuning/RAG  MLOps Deployment).

·         Expert proficiency in JIRA, Confluence, Miro, or Azure DevOps configured for custom AI workflow tracking.
Familiarity with AI guardrails, model validation processes, data privacy compliance, and production testing approaches.

Preferred / Nice-to-Have Skills

·         Familiarity with MLOps frameworks, LLM deployment pipelines, or vector databases.

·         PMI-ACP, SAFe POPM, or Agile Coaching certifications.

·         Background in software engineering, data engineering, or technical project management.

·         Experience navigating cloud AI ecosystems (AWS SageMaker, Azure OpenAI, Google Cloud Platform Vertex AI).