Sr. Manager, Full-Stack AI Engineering; Remote from Houston or Austin TX

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• Career Growth:
  Advance your career with opportunities for leadership and personal development.
• Culture of Excellence:
  Be part of a supportive team that values your input and encourages innovation.
• Competitive Benefits:
  Enjoy a comprehensive benefits package that looks after both your professional and personal needs.

Our Total Rewards package underscores our commitment to recognizing your contributions. We offer a competitive and fair compensation structure that includes base pay and performance-based rewards. Compensation is based on skill set, experience, qualifications, and job-related requirements. Our comprehensive benefits package includes medical, dental, and vision insurance, wellness programs, retirement plans, and generous paid leave. Discover more about what we offer by visiting our Benefits page.

The Sr. Manager, Full-Stack AI Engineering, a technical engineering manager, leads a team of Full-Stack AI Engineers that design and build enterprise-grade applications that operationalize analytical models/engines, machine learning models/systems, Gen AI solutions from data integration pipelines, backend APIs, optimization engine, AI Agents to front-end and AI-powered web application. This role stays hands-on, directly contributing to software engineering technology stack, system design pattern, development & deployment playbooks, and engineering work on active projects.

The Sr. Manager reports directly to the Director, Data Science, and partners closely with product owners, data engineers, and AI scientists on various AI/analytical oriented projects. People management responsibilities include hiring, coaching, performance management, and setting engineering standards across the team.

As a Sr Mgr, Full-Stack AI Eng you will:

• Team Leadership & People Management
  • Directly manage a team of Full-Stack AI Engineers across multiple concurrent project pods.
  • Conduct regular 1:1s, provide ongoing coaching and feedback, set clear performance expectations, and lead formal performance reviews.
  • Build a high-performing, accountable team culture that takes pride in quality and delivery.
• Hands-On Engineering
  • Actively contribute as a Full-Stack AI Engineer on project work alongside the team.
  • Design end-to-end architecture spanning frontend, backend, and data layers.
  • Design and build data pipelines, backend APIs, AI-powered features, and front-end applications using the same stack and standards expected of the team. Maintain technical depth across the stack to provide credible guidance, conduct meaningful code reviews, architecture review and set a high bar for engineering quality through example.
• Engineering Standards & Quality
  • Define and enforce engineering standards across the team — covering code quality, testing practices, security, documentation.
  • Conduct or oversee solution architecture, code reviews and documentation reviews on high-impact work.
  • Stay current on AI tooling advancements and share best practices across the team.
  • Ensure that AI-generated code meets the same quality bar as hand-authored code.
  • Champion the effective and responsible use of AI coding tools across the team. Develop and formulate spec-driven AI coding practice with responsible use of AI coding tools (Claude Code, Codex, Augment Code, etc.).
  • Evaluate new tools and practices, establish team-wide norms for AI-assisted development, and ensure engineers are using these tools in ways that increase quality and delivery confidence — not just speed.
• Technical Guidance & Architecture
  • Provide hands-on technical guidance to engineers on solution design, full-stack architecture, AI and LLM integration patterns, and Databricks platform usage. Participate in architecture reviews and contribute to key technical decisions. Remain close enough to the work to…