Engagement Manager

Turing • Dallas, TX

2d

About The Position

Turing Intelligence builds and ships production AI systems for large enterprises in banking, capital markets, asset management, and insurance. The Engagement Manager owns client outcomes from signed statement of work through production deployment, adoption, and renewal. The role serves as the client's day-to-day executive counterpart, leads a pod of Forward Deployed Engineers and delivery staff, 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 manager does not write code but must have enough technical fluency to scope AI work, challenge engineering plans, and explain trade-offs to client technical and model-risk stakeholders.

The manager builds senior client relationships, leads steering committees and executive communications, and anticipates client needs and stakeholder dynamics. They incorporate regulated-enterprise requirements—including model risk management, information security, data residency, procurement, legal, and Responsible AI—into delivery planning, and address delivery problems transparently with a plan.

The role owns engagements end to end, including SOW structure, scope, milestones, dependencies, acceptance criteria, value hypotheses, delivery cadence, staffing, risks, decisions, client communications, and scope and priority decisions. Success is measured by adoption and impact, with baselines and KPIs defined up front. The manager partners with the engineering lead to establish production-readiness, model evaluation, and acceptance-testing standards.

The Engagement Manager owns engagement financials against revenue and margin targets, including staffing mix, utilization, change orders, scope control, forecasting, and early variance reporting. They identify expansion opportunities and partner with the BFSI GM, who owns the account relationship and topline revenue. They also lead delivery teams, collaborate on architecture and staffing decisions, and develop reusable BFSI delivery playbooks, estimation models, and SOW patterns.

Requirements

• Collaborative leadership instincts, ability to motivate teams under delivery pressure, and a role-model standard of work ethic, accountability, and client commitment.
• At least 8 years of client-facing delivery or consulting experience.
• At least 3 years leading engagements or accounts for financial services clients, including banking, capital markets, asset management, insurance, or payments.
• Track record owning engagement or account financials, including margin, forecasting, staffing, change orders, and renewals.
• Experience leading at least one AI, ML, or data-platform program into production at an enterprise, and ability to describe the resulting client change.
• Executive presence and experience running steering committees, managing MD-level sponsors, and retaining accounts through difficult periods.
• Technical fluency to read architecture diagrams, understand how LLM-based systems are 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 within a bank or insurer's 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 working alongside a commercial account owner.

Responsibilities

• Serve as the trusted client counterpart, lead steering committees and executive updates, and handle difficult conversations.
• Understand client business needs, organizational dynamics, and stakeholder influence to anticipate and advance initiatives.
• Plan for regulated-enterprise requirements, including model risk management, information security, data residency, procurement, legal, and Responsible AI.
• Protect client relationships during delivery problems by communicating bad news early and presenting a plan.
• Own engagements from SOW through production, structuring scope, milestones, dependencies, acceptance criteria, and value hypotheses.
• Manage engagement cadence, staffing, risks, dependencies, decision logs, and client communications; make scope and priority decisions to protect the critical path.
• Define baselines and KPIs up front and report on adoption and measured impact.
• Set production-readiness, model evaluation, and acceptance-testing quality standards with the engineering lead.
• Manage engagement P&L against revenue and margin targets, including staffing mix, utilization, change orders, scope creep, forecasting, and variance reporting.
• Identify and shape expansion opportunities, follow-on SOWs, and renewals in partnership with the BFSI GM.
• Report delivered value, risks, and key decisions to client sponsors and Turing leadership on a fixed cadence.
• Lead a pod of Forward Deployed Engineers and delivery staff, setting direction, unblocking the team, and maintaining client-facing professionalism and delivery discipline.
• Partner with the technical lead on architecture and staffing decisions while remaining accountable for outcomes.
• Develop reusable BFSI delivery playbooks, estimation models, and SOW patterns.

Benefits

• Opportunity to work at the frontier of AI with leading AI labs.
• Opportunity to contribute to AI research and showcase work at conferences such as ICLR, ICML, and NeurIPS.
• Opportunity to apply frontier AI innovations to enterprise business challenges.
• Collaboration with colleagues with AI experience from companies including Google, Meta, and Amazon.
• Startup pace, ownership, and impact.

What This Job Offers

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