Client Engagement Lead - Pharma & Life Sciences

Turing • New York, NY

1d • Hybrid

About The Position

Turing Intelligence builds and ships production AI systems for large enterprises. The Client Engagement Lead owns client engagements from signed statement of work through production deployment, adoption, and renewal. This person serves as the client’s day-to-day executive counterpart, leads a pod of Forward Deployed Engineers and delivery staff, and owns engagement scope, timeline, margin, and expansion. The role is an account delivery leadership position rather than a project-management or engineering seat; it requires technical fluency to scope AI work, challenge engineering plans, and explain trade-offs to senior technical and risk stakeholders, but does not require writing code.

The role leads client relationships, end-to-end delivery, engagement financials and growth, and team leadership. It involves defining measurable success, managing regulated-enterprise requirements, ensuring production quality and adoption, protecting engagement margins, and identifying expansion opportunities in partnership with the BFSI General Manager. The position is hybrid, based in the New York metro area, with client onsite work several days per week as needed and occasional travel to other client sites. It reports to the Head of AI Delivery, Turing Intelligence.

Requirements

• Collaborative engagement leadership, sound leadership instincts, ability to motivate teams under delivery pressure, and role-model work ethic, accountability, and client commitment.
• At least 8 years of client-facing delivery or consulting experience, including 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.
• Experience leading at least one AI, ML, or data-platform program into enterprise production, with the ability to explain what the client changed as a result.
• Executive presence and relationship depth, including running steering committees, managing MD-level sponsors, and retaining accounts through difficult periods.
• Technical fluency sufficient to read architecture diagrams, understand how an LLM-based system is built and evaluated, and identify weaknesses in proposed 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 inside 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 counterpart to client sponsors, from working teams through managing directors and C-suite; lead steering committees, executive updates, and difficult conversations.
• Understand client business, organization, and stakeholder dynamics to anticipate needs and navigate decision-making.
• 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 problems by communicating issues early and presenting a plan.
• Own engagements end to end, structuring statements of work with clear scope, milestones, dependencies, acceptance criteria, and a value hypothesis before signature.
• Run engagement cadence, staffing, risk and dependency management, decision logs, and client communications; make scope and priority decisions that protect the critical path.
• Define baselines and KPIs upfront and report measured adoption and impact, rather than treating on-time delivery alone as success.
• 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 Intelligence 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 owning engagement outcomes.
• Develop reusable BFSI delivery playbooks, estimation models, and SOW patterns.

Benefits

• Base salary plus bonus and equity.
• Opportunity to work at the frontier of AI and help leading AI labs improve advanced models through expert datasets, reinforcement learning environments, and benchmarks.
• Opportunity to contribute to AI research and showcase work at conferences such as ICLR, ICML, and NeurIPS.
• Opportunity to bring frontier AI innovation to enterprise business challenges.
• Collaboration with colleagues with AI experience from leading technology companies.
• Startup pace, ownership, and impact.

What This Job Offers

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