Sr. Manager, Full-Stack AI Engineering

Living Our Values All associates are guided by Our Values. Our Values are the unifying foundation of our companies. We strive to ensure that every decision we make and every action we take demonstrates Our Values. We believe that putting Our Values into practice creates lasting benefits for all of our associates, shareholders, and the communities in which we live. Why Join Us 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. Total Rewards 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. A Day In The Life 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 assess complexity, quality, and risk. Hiring & Talent Development Partner with the Director of Data Science and HR to define hiring needs, assess candidates, and define learning path of each team member to grow the team. Develop engineers through structured feedback, stretch assignments, and learning opportunities. Build a team with complementary strengths across cloud engineering, including frontend, backend, data integration, DevOps/InfraOps, ML system integration and AI tooling. Stakeholder Partnership Work closely with product owners, data engineers, AI scientists, and the Director of Data Science to align on engineering priorities and delivery. Communicate team capacity and technical constraints clearly. Represent the engineering team’s perspective in cross‑functional planning discussions. Process & Operational Excellence Establish and continuously improve the team's engineering processes: sprint cadences, code review workflows, support processes, and knowledge sharing. Identify systemic inefficiencies and drive improvements that make the team more effective over time. What We Need From You Bachelor's Degree in Computer Science, Software Engineering, Information Systems, or a related technical field. 10+ years Software engineering experience with a strong full-stack background. 5+ years of experience leading or managing software engineering teams. Demonstrated ability to hire, develop, and retain engineering talent. Experience setting and enforcing engineering standards across a team (code review, testing, documentation, security). Experience delivering AI or data-intensive applications in a production environment. Hands‑on experience engineering a development workflow using AI coding tools (Claude Code, Codex, Augment Code, or equivalent). Experience with full-stack web development (frontend frameworks such as React or Angular; Python-based backends such as FastAPI, Django, or Flask). Experience managing delivery across multiple concurrent projects or workstreams. Experience with CI/CD, cloud-native deployments, or infrastructure-as-code (AWS preferred). Experience integrating LLMs, RAG pipelines, or agentic AI frameworks into production applications (Preferred). Experience with Databricks or Lakehouse architectures (Preferred). Experience working in agile/scrum delivery models with cross‑functional teams including data scientists and product owners (Preferred). Technical credibility: depth sufficient to assess code quality, architectural decisions, and engineering complexity without being a bottleneck. People leadership: ability to coach, develop, and hold engineers accountable in a way that builds trust and improves performance over time. Delivery ownership: takes accountability for team output, proactively manages risks, and communicates status clearly to stakeholders. AI tooling judgment: understands both the capabilities and limitations of AI coding tools and can set meaningful standards for their use. Strong cross‑functional collaboration: comfortable working alongside product owners, data engineers, AI scientists, and business stakeholders. Ability to operate in a fast-moving environment where priorities shift and the tooling landscape evolves rapidly. Clear and direct communicator: able to translate technical constraints into language that non-technical stakeholders can act on. Process pragmatism: improves team processes where it matters, avoids overhead where it doesn't. Physical and Environmental Requirements The physical requirements described here are representative of those that must be met by an associate to successfully perform the essential functions of the job. While performing the duties of the job, the associate is required on a daily basis to analyze and interpret data, communicate, and remain in a stationary position for a significant amount of the work day and frequently access, input, and retrieve information from the computer and other office productivity devices. The associate is regularly required to move about the office and around the corporate campus. The associate must frequently move up to 10 pounds and occasionally move up to 25 pounds. Travel Requirements 20%-30%: The position is open to in‑office and remote work in Houston or Austin. If remote (>50 miles from office) it is expected that the associate will be in office at least 4 days a month. This may vary based upon project meetings and events. Equal Employment Opportunity The Friedkin Group and its affiliates are committed to ensuring equal employment opportunities, including providing reasonable accommodations to individuals with disabilities. If you have a disability and would like to request an accommodation, please contact us at View email address on click.appcast.io. We celebrate diversity and are committed to creating an inclusive environment for all associates. We are seeking candidates legally authorized to work in the United States, without sponsorship. #J-18808-Ljbffr The Friedkin Group