Scrum Master - Dallas, TX
About The Position
This job description is tailored for a Scrum Master who understands that building Agentic AI products isn’t like traditional software development. It requires managing the uncertainty of LLM outputs, data-dependency loops, and the iterative nature of autonomous agent orchestration. We are seeking a seasoned Scrum Master to lead cross-functional squads in the delivery of Agentic AI products. In this role, you will go beyond traditional Agile facilitation. You will manage the unique lifecycle of AI agent development—incorporating prompt engineering, multi-agent orchestration, and autonomous tool-use—while serving as the primary bridge between our technical team and the end customer. Your mission is to ensure the team remains focused on high-value outcomes while navigating the experimental and non-linear nature of AI model performance and evaluation.
Requirements
- Experience: 5+ years as a Scrum Master, with at least 1–2 years specifically working on Generative AI or Machine Learning projects.
- Certification: CSM (Certified Scrum Master) or PSM I/II is required.
- AI Literacy: Solid understanding of the Agentic AI landscape (e.g., LLMs, LangChain/LangGraph, AutoGen, vector databases, and autonomous agents).
- Adaptive Mindset: Ability to pivot when a model experiment fails and guide the team through "fail-fast" iterations.
- Tooling Proficiency: Expert knowledge of Jira/Confluence (specifically setting up custom workflows for AI experiment tracking) and familiarity with AI evaluation tools.
- Soft Skills: Exceptional negotiation skills to manage the tension between technical R&D and customer delivery deadlines.
Nice To Haves
- Technical background in Software Engineering or Data Science.
- Experience with multi-agent orchestration frameworks.
- Familiarity with Cloud platforms (AWS, Azure, or GCP) and their AI/ML service suites.
Responsibilities
- Agile Facilitation & Delivery: Lead all standard Scrum ceremonies (Daily Stand-ups, Sprint Planning, Reviews, and Retrospectives) with a focus on adapting Agile to the AI/ML lifecycle.
- Agentic Workflow Management: Help the team manage the complexities of "Agentic" development, including multi-agent handoffs, "human-in-the-loop" requirements, and RAG (Retrieval-Augmented Generation) pipelines.
- Removing AI-Specific Blockers: Proactively identify and resolve bottlenecks unique to AI, such as data availability, GPU/compute constraints, API rate limits, and model "hallucination" cycles.
- Customer Stakeholder Management: Act as the primary point of contact for the customer. Educate them on the iterative nature of AI development and manage expectations regarding model accuracy vs. project timelines.
- Backlog Refinement: Partner with Product Owners to translate vague "AI agent" concepts into actionable user stories with clear acceptance criteria (e.g., specific evaluation metrics or success rates).
- Metrics & Reporting: Track traditional metrics (Velocity, Burndown) alongside AI-centric health indicators (Model evaluation scores, latency targets, and cost-per-token efficiencies).
Benefits
- Medical, vision, and dental benefits
- 401k retirement plan
- variable pay/incentives
- paid time off
- paid holidays are available for full time employees.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
Number of Employees
5,001-10,000 employees
