Sr Manager, Forward Deployment Engineer

Sr Manager, Forward Deployment Engineering

T-Mobile's Forward Deployment Engineering practice embeds engineers directly inside our business units to ship production agentic AI solutions. The Sr Manager, Forward Deployment Engineering leads the management layer of that practice. You oversee multiple FDE pods across business domains, each one a high-performing innovative team building and deploying real agentic solutions against real business problems, measured by validated ROI.

You'll need to be technical enough to earn the respect of Senior and Principal FDEs, and credible enough with business leaders to own relationships at the Director and VP level. Performance is measured on aggregate ROI outcomes across pods and on the health of the FDE team you build.

Job Responsibilities:

• Technical Guidance & Strategic Presence:
  Accountable for the technical quality of what the practice ships. Guide direction on high-stakes agentic AI delivery decisions, architectural trade-offs, and cross-domain patterns. Stay close enough to pod teams to hold technical credibility and catch systemic delivery issues before they become domain failures. Ensure responsible AI and data security standards are embedded in practice-level delivery.
• Cross-Pod Coordination & Resource Management:
  Accountable for the practice having the right people in the right domains. Own allocation and domain assignment planning across pods, identify resourcing imbalances early, and manage headcount planning and the hiring pipeline in coordination with BU leaders and the Sr Director.
• Senior BU Relationship Management:
  Accountable for BU leadership trusting the practice with their hardest problems. Serve as the senior point of contact at the Director and VP level — escalating structural blockers, negotiating domain prioritization, aligning the FDE roadmap with BU strategic objectives, and representing validated ROI outcomes in senior leadership forums
• Practice Health & Delivery Standards:
  Accountable for the long-term health of the practice itself. Own practice-level metrics — aggregate ROI, FDE retention, domain assignment health, delivery quality — and set the responsible AI, data security, and privacy standards every FDE deliverable is held to. Partner with TPMs and CoE leadership to keep requirements intake and delivery handoffs running effectively.
• FDE Pod Performance:
  Accountable for every pod in the practice delivering validated ROI and growing the people in it. Directly manage FDE pods across multiple BU stakeholders — coaching, performance feedback, and career development — with visibility into each pod's delivery health, ROI performance, and team morale through structured check-ins and regular engagement.

Required Education and

Work Experience:

• Bachelor's Degree Computer Science, Software Engineering, Data Science, or related technical field. Master's Degree preferred. Relevant equivalent experience accepted.
• 7-10 years Total experience in technical and people leadership roles combined, including 5+ years of progressive people management experience with demonstrated ability to manage other managers or senior technical leads. Hands-on production engineering foundation required. Track record of leading technical teams to measurable business outcomes in ambiguous delivery environments.
• More than 10 years Candidates with 10+ years of combined technical and leadership experience preferred. Ideal background includes having built or scaled a forward deployment, solutions engineering, or embedded technical practice, and experience managing multi-domain programs with rotating team or project structures. (Preferred)

Required

Knowledge, Skills and Abilities:

• Technical Depth & Credibility:
  Sufficient hands-on AI/ML engineering background to guide strategic technical decisions, evaluate engineering quality, and maintain credibility with Senior and Principal FDEs. Must be technically fluent. Familiarity with LLM deployment patterns including RAG architecture, prompt orchestration, and multi-agent system design. Exposure to agentic frameworks (Lang Chain, Llama Index, Auto Gen, or similar) and cloud-native infrastructure (AWS primary). Working knowledge of MCP…