AI Deployment Lead – GTM

Jobtailor; San Francisco (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Jobtailor seeks an experienced engagements leader to drive discovery, design end-to-end delivery, and shape AI-driven product features for clients in regulated environments.

You will translate business needs into technical specs, onboard stakeholders, and manage change across large enterprise accounts to deliver measurable outcomes.

Qualifications

• 10+ years of professional experience.
• Background in top-tier consulting or private equity or AI/product environments.
• Experience leading discovery with clients and managing senior stakeholders.
• Commercial instinct: pricing and growing accounts.
• Proven success driving organizational change at scale.
• Comfort with AI/ML concepts and translating them for business audiences.
• Strong communication and storytelling skills.
• Ability to operate across customer work, analysis, and operations in ambiguity.

Responsibilities

• Run discovery and engagement operations with customers.
• Own end-to-end delivery from kickoff to adoption.
• Define and prioritize AI-driven product features.
• Translate business needs into technical specifications for engineering teams.
• Drive adoption and change management across stakeholders.
• Lead program delivery and commercial expansion within accounts.
• Support AI diligence and value creation for target companies.
• Bridge business and technology for investment committees and executives.
• Collaborate cross-functionally with data scientists, engineers, and product leads.

Skills

Client engagement

Discovery

Delivery leadership

Cross-functional

AI/ML fluency

Stakeholder management

Change management

Commercial acumen

Communication

Job description

Responsibilities

• Run discovery and engagement operations, leading structured discovery with customers, developing value sizing and product proposals, mapping their needs, and running the day‑to‑day rhythm of an engagement so nothing falls through the cracks.
• Own end‑to‑end delivery: own your engagements from kickoff to adoption, lead delivery sprints and deployment timelines, coordinate the cross‑functional delivery team, and ensure timely, high‑quality, audit‑ready solutions in regulated environments.
• Define and prioritize features: partner with clients to identify high‑impact problems across their workflows, and define the AI‑driven product features that address them.
• Translate business needs: convert customer requirements and operational pain points into clear technical specifications and use cases for internal engineering teams.
• Drive adoption and change management: onboard stakeholders and engage users, lead the people‑and‑process change required for new ways of working to take hold, and gather direct feedback to drive continuous improvement.
• Drive program success and commercial expansion: partner with the client to deliver measurable program outcomes, and own the commercial agenda within each account, building the trust and impact that expand our relationship over time.
• Support AI diligence and value creation: contribute to deep‑dive assessments of target companies’ AI strategies, data infrastructure, and technical maturity, and help shape plans that connect AI capabilities to commercial outcomes.
• Bridge business and technology: translate complex AI/ML capabilities into actionable recommendations for investment committees, portfolio executives, and senior client stakeholders.
• Collaborate cross‑functionally: serve as the bridge between customers and internal teams, including data scientists, engineers, and product leads.

Requirements

• 10+ years of professional experience.
• A background in top‑tier consulting (McKinsey, Bain, BCG), private equity, investment banking, AI/product companies (e.g., Palantir, Google, Amazon), or technical and operating roles at large enterprises or financial institutions.
• Experience working with customers or clients, leading discovery, building trust, and navigating senior stakeholders.
• Commercial instinct and/or experience, thinking through value, pricing, and what it takes to win and grow an account, not just the analysis.
• Demonstrated success driving both people and process change at large enterprises — operating‑model redesign, workflow transformation, and adoption at scale, not just software rollouts.
• Comfort with AI and technical concepts, able to work closely with product and engineering and translate between technical and business audiences.
• Strong communication and building skills. Ability to turn complex analysis into clear narratives and high‑quality materials that move decisions.
• Range and ownership. Comfort moving between customer work, analysis, and operations, and thriving in ambiguity: can take things 0 to 1 without waiting for a playbook.