AI Deployment Strategy Lead

AI Deployment Strategy Lead Position Summary We are looking for an experienced deployment-focused technical leader to join an AI and optimization team. This role is responsible for maximizing the impact and scalability of customer deployments by shaping how solutions are deployed—not only what is built. As an AI Deployment Strategy Lead, you will define deployment approaches, engagement models, and delivery strategies that enable AI, optimization, analytics, and data-driven solutions to scale across customers and industries. You will operate at the intersection of customer problem framing, technical pre-sales, solution feasibility, scope definition, deployment planning, and delivery risk management. This position sits within a Professional Services organization and involves close collaboration with forward-deployed engineers, data scientists, software engineers, developers, solution architects, sales teams, and other technical stakeholders. Your objective will be to ensure customer engagements are technically feasible, appropriately scoped, commercially executable, and aligned with measurable business outcomes. Key Responsibilities Define deployment patterns, archetypes, and engagement models that enable repeatable and scalable delivery across customers and use cases. Determine which solution components should be customized, standardized, or productized to maximize long-term customer impact, efficiency, and reuse. Support technical pre-sales engagements by evaluating solution feasibility, delivery complexity, implementation risks, dependencies, and deployment approaches. Translate customer requirements into clear project scopes, delivery plans, assumptions, dependencies, milestones, and resource estimates. Partner with sales and delivery teams to develop executable technical and commercial proposals. Build and support technical demonstrations, prototypes, proofs-of-concept, and deployment narratives in collaboration with engineering and technical teams. Help customers clearly define business objectives, success metrics, operational constraints, and key assumptions early in the engagement lifecycle. Challenge ambiguous, low-leverage, or poorly aligned customer requests and reframe them around measurable business value. Anticipate technical, organizational, operational, and delivery risks and ensure project scope remains aligned with customer outcomes. Establish scalable approaches for moving solutions from proof-of-concept into production and repeatable deployment. Collaborate across multidisciplinary and geographically distributed teams to ensure effective execution. Balance customer-specific requirements with opportunities for standardization, reuse, and long-term productization. Basic Qualifications Bachelor's, Master's, or PhD degree in engineering, computer science, data science, operations research, business, or another quantitative or technical discipline. Experience in consulting, solution delivery, technical pre-sales, deployment strategy, product implementation, professional services, or a comparable client-facing technical role. Demonstrated ability to translate ambiguous customer needs into clearly defined problem statements, success metrics, technical requirements, delivery plans, and project scope. Strong communication and stakeholder-management skills, with the ability to explain technical trade-offs, deployment risks, and business implications to both technical and non-technical audiences. Experience evaluating technical feasibility, delivery complexity, implementation effort, and risk for customer-facing solutions. Strong organizational and project-management skills, with the ability to manage multiple customer engagements, deliverables, and internal stakeholders simultaneously. Ability to operate effectively in cross-cultural, geographically distributed, and multidisciplinary teams. Strong judgment and problem-solving skills in ambiguous and rapidly changing environments. Preferred Qualifications Experience supporting enterprise deployments involving AI, machine learning, data, optimization, analytics, or digital transformation. Experience with enterprise data, analytics, application-development, or deployment platforms such as Palantir Foundry or comparable technologies. Experience developing technical demonstrations, prototypes, proofs-of-concept, or pilot solutions for enterprise customers. Experience contributing to statements of work, project plans, delivery estimates, implementation assumptions, or commercial proposals. Experience working with field deployment engineers, product teams, sales teams, solution architects, data scientists, or software engineering teams. Experience taking customer requirements from initial discovery through technical scoping and executable delivery planning. Comfort operating in ambiguous environments and applying sound judgment to balance customization, standardization, scalability, and productization. Experience identifying opportunities to create repeatable deployment patterns across customers or industries.

Define scalable deployment patterns and engagement models to maximize the impact of AI and optimization solutions for customers. Lead technical pre-sales, scope definition, and risk management to ensure engagements are commercially executable and aligned with business outcomes.

Requires a degree in a quantitative field and experience in technical pre-sales, consulting, or professional services. Candidates must demonstrate the ability to translate ambiguous customer needs into technical requirements and delivery plans.

Relevées dans la description du poste. Confirmez les exigences importantes ci-dessus.

• AI Deployment Strategy
• Technical Pre-sales
• Solution Architecture
• Project Scoping
• Stakeholder Management
• Risk Management
• Proof-of-Concept Development
• Deployment Planning
• Business Value Framing
• Enterprise Software Implementation
• Data Science
• Optimization
• Professional Services
• Technical Consulting
• Resource Estimation
• Productization

• Consulting
• Data & Analytics
• Management & Leadership
• Technology
• Software

Formation minimale

Baccalauréat

Expérience minimale

5+ ans

Postuler avant le

11 sept. 2026

Langue de l’offre

anglais

Heures de travail

40 heures par semaine

Niveau d’expérience

Mid-Senior level

Mode de candidature

La candidature directe est offerte