Engagement Manager

Turing • Dallas, TX

2d

About The Position

Turing Intelligence builds and deploys production AI systems for large enterprises, including clients in banking, capital markets, asset management, and insurance. The Engagement Manager owns client engagements from signed statement of work (SOW) through production deployment, adoption, and renewal. This role is the client's day-to-day executive counterpart, leads a pod of Forward Deployed Engineers (FDEs), and is accountable for engagement scope, timeline, margin, and expansion. It is an account delivery leadership position rather than a project-management or engineering role. The Engagement Manager does not write code, but needs the technical fluency to scope AI work, challenge engineering plans, and explain trade-offs to client technical and risk stakeholders.

The role owns client relationships and executive communications; end-to-end delivery, including SOW structure and production outcomes; engagement financials and growth; and leadership of FDE and delivery teams. Success is measured by adoption and measurable impact, as well as delivery and commercial commitments. The position partners with the BFSI GM, who owns the account relationship and topline revenue, while the Engagement Manager owns delivery and engagement growth.

Turing describes its work as building high-quality datasets, reinforcement-learning environments, research benchmarks, and end-to-end agentic AI systems for frontier AI labs and Fortune 500 enterprises. Its stated values are client first, startup speed, and AI forward. Turing is an equal opportunity employer and encourages applicants whose experience may not align with every qualification to apply.

Requirements

• Collaborative engagement manager with sound leadership instincts who motivates teams under delivery pressure and leads by example in work ethic, accountability, and client commitment.
• 8+ years of experience in client-facing delivery or consulting.
• At least 3 years leading engagements or accounts for financial services clients in banking, capital markets, asset management, insurance, or payments.
• Track record of owning engagement or account financials, including margin, forecasting, staffing, change orders, and renewals.
• Led at least one AI, ML, or data-platform program into production at an enterprise and can explain what the client changed as a result.
• Executive presence and relationship depth, including experience running steering committees, managing MD-level sponsors, and retaining accounts through difficult periods.
• Technical fluency to read an architecture diagram, understand how an LLM-based system is built and evaluated, and identify weaknesses in plans; coding is not required.
• Based in the New York metro area and able to be onsite with clients several days per week.

Nice To Haves

• Engagement management experience at a technology consultancy, systems integrator, or AI-native delivery firm, or delivery leadership experience in a bank or insurer technology or data organization.
• Familiarity with BFSI regulatory context, including model risk management, information security and third-party risk, and data privacy and residency.
• Experience in a two-in-a-box model alongside a commercial account owner.

Responsibilities

• Serve as the trusted day-to-day executive counterpart to client sponsors, from working teams through managing directors and C-suite.
• Own client steering committees, executive updates, and difficult conversations; understand client business, organizational dynamics, and stakeholders.
• Plan for regulated-enterprise requirements, including model risk management, information security review, data residency, procurement, legal, and Responsible AI requirements.
• Protect client relationships during delivery issues by communicating problems early and bringing a plan.
• Own engagements end to end, structuring SOWs with clear scope, milestones, dependencies, acceptance criteria, and a value hypothesis before signature.
• Manage engagement cadence, staffing, risks, dependencies, decision logs, and client communications.
• Make scope and priority decisions to protect the critical path, and drive adoption and measured impact rather than delivery timing alone.
• Define baselines and KPIs up front and report results against them.
• Set production-readiness, model-component evaluation, and acceptance-testing standards with the engineering lead.
• Own engagement P&L against revenue and margin targets; manage staffing mix, utilization, change orders, and scope creep to protect gross margin.
• Forecast accurately and flag financial variance early.
• Identify and shape expansion opportunities, including new use cases, adjacent business units, follow-on SOWs, and renewals; partner with the BFSI GM to convert them.
• Report delivered value, risks, and key decisions to client sponsors and Turing leadership on a fixed cadence.
• Lead a pod of FDEs and delivery staff, setting direction, removing blockers, and maintaining client-facing professionalism and delivery discipline.
• Partner with the technical lead on architecture and staffing decisions while owning the engagement outcome.
• Develop reusable BFSI delivery playbooks, estimation models, and SOW patterns.

Benefits

• Opportunity to work at the frontier of AI with leading AI labs on expert datasets, reinforcement-learning environments, and benchmarks.
• Opportunity to contribute to leading-edge AI research and showcase work at conferences such as ICLR, ICML, and NeurIPS.
• Opportunity to apply frontier AI innovation to enterprise business challenges.
• Collaboration with colleagues with AI experience from Google, Meta, Amazon, and other leading technology companies.
• Startup-like speed, ownership, and impact.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed