Strategic Builder

Leadout Capital; Mumbai; On-site; INR 1,800,000 - 3,000,000; Full time

Job summary

Salesforce is seeking Deployment Strategists to act as customer-facing advisors, shaping AI strategy and driving adoption for enterprise clients. You will translate complex challenges into agentic AI deployments that go live and deliver measurable value.

Responsibilities include end-to-end engagement ownership, AI strategy workshops, and coordinating with engineers to ensure successful delivery and ongoing value realization for customers.

Qualifications

• 10-15 years of total experience with 5 years in Data & AI for strategic solutioning or delivery leadership.
• Degree in Computer Science or related field required.
• Prior customer-facing delivery experience is required.

Responsibilities

• Lead end-to-end customer engagements across the value lifecycle: Identify → Commit → Deploy → Consume.
• Define AI strategy and architecture; lead workshops and design sessions.
• Oversee deployment timelines, risk, and stakeholder communication; act as the delivery backbone.
• Own adoption, consumption, and expansion metrics within engagements; drive value realization.
• Coordinate with Forward Deployed Engineers to align strategy with technical execution.
• Develop customer solutions supported by AI tools (Cursor, Claude, Vibes).
• Manage customer-facing relationships with senior stakeholders and present business value.

Skills

Client-facing

Strategic advisory

AI strategy

Program management

Cross-functional leadership

Architecture workshops

Education

Bachelor's degree in Computer Science or related field

Tools

Data Cloud

Agentic AI platform

Vibes

Cursor

Claude

Job description

The Experience

Customer impact from day one. Strategic clarity and Execution that sticks.

Salesforce is hiring Deployment Strategists — Strategic Builders who are customer-facing advisors, who define AI strategy, shape agentic solutions, and drive measurable adoption for enterprise customers. You'll work as part of a delivery team alongside Forward Deployed Engineers, translating complex business challenges into agentic AI deployments that go live and generate real value.

Engagements are focused and time-bound — typically 12 weeks or less — and may span a single strategic account or multiple customers simultaneously. Your impact isn't just getting to deployment. It ensures customers realise lasting, scalable value from the solutions your team builds.

What You'll Actually Be Doing

• Full Lifecycle Ownership: Lead end-to-end customer engagement across the complete value lifecycle — Identify → Commit → Deploy → Consume — owning outcomes at every stage, not just discovery or deal closure
• AI Strategy & Architecture: Define the customer's Agentic AI strategy and roadmap. Lead design workshops, agent design sessions, and jobs-to-be-done analysis. Architect solutions spanning Salesforce's agentic AI platform, Data Cloud, and enterprise systems, with responsible AI governance baked in from the start.
• Deployment Oversight & Program Management: Manage engagement delivery end-to-end timelines, stakeholder communication, risk escalation, and progress reporting. You are the operational backbone of your delivery team, ensuring nothing falls through the cracks.
• Adoption & Consumption: Own adoption, consumption, and expansion metrics within your engagement scope. Identify blockers early and develop strategies to drive measurable value realization
• Delivery Team Coordination: Partner closely with the Forward Deployed Engineers on your team to align strategy with technical execution. Keep the team focused, unblocked, and on track to hit delivery milestones.
• AI-Supported Development: You'll be developing real customer solutions supported by leading-edge AI tools: Including
• Cursor, Claude, and our coding products like Vibes, to accelerate development.
• Customer Stakeholder Management: Serve as the primary customer-facing contact, building trust-based relationships with senior stakeholders and present proposals, decisions and outcomes in terms of business value, not just technical detail.
• AI Readiness: Assess customer readiness for AI adoption and guide change management and process transformation to maximise the benefits of intelligent agents
• Product Feedback Loop: Synthesise field insights and translate them into actionable product feedback that influences Salesforce's Agentic AI platform roadmap.

You're Our Person If...

• 10-15 years of total experience with relevant 5 years into Data & AI in strategic solutioning, technical advisory, or delivery leadership or program management for enterprise cloud or SaaS technology
• You have a degree in Computer Science or a related field
• Prior customer-facing delivery experience (consulting, professional services, or technical advisory) - this is a requirement, not a nice-to-have
• Demonstrated understanding of the Salesforce platform and ecosystem, including Agentic AI capabilities and Data Cloud
• Working knowledge of one or more programming languages: Python, JavaScript, Java, or Apex
• Proven ability to lead and own complex, ambiguous engagements end-to-end — from discovery through to measurable outcomes
• Experience leading AI/LLM solution design, including agentic AI strategy, conversation design, and responsible AI practices
• Strong project and program management skills — ability to run multiple workstreams, manage stakeholder expectations, and keep delivery on track in ambiguous environments
• Ability to travel 25% of the time to customer sites

Even Better If...

• Experience with Salesforce Data Cloud, Agentforce platform, and Salesforce CRM (Sales, Service, Marketing)
• Experience designing and deploying AI solutions in regulated industries (e.g., public sector, financial services, healthcare)
• Salesforce platform certifications (e.g., Data Cloud Consultant, Agentforce Specialist, Application Architect) or similar platform certifications such as Microsoft, Oracle, or similar platforms.
• Background in change management, organisational design, or enterprise transformation
• Experience with AI/ML concepts beyond LLMs, including NLP, RAG architectures, and model evaluation frameworks
• A get-things-done mindset with strong bias for action — comfortable operating in unstructured fast moving environments