Forward Deployed Engineer
Role details
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Tech stack
Job description
We are seeking a Strategic Builder - a senior technical advisor and lifecycle owner who leads customers through the full Agentforce value journey, from initial use case identification through to active consumption and expansion. Strategic Builders operate by embedding with customers to define AI strategy, architect agentic solutions, and drive measurable business outcomes.
As a trusted partner, you will bridge customer's strategic ambition with Salesforce's AI and data capabilities, orchestrating pod delivery and ensuring deployments translate into sustained, scalable value. You will also serve as a critical product feedback loop, bringing field insights directly back to the Salesforce Engineering and Product teams., * 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. Architect end-to-end solutions spanning Agentforce, Data Cloud, and enterprise systems. Lead design workshops, agent design sessions, and jobs-to-be-done analysis and responsible AI governance. Define end-to-end AI and platform solution strategies aligned to customer outcomes
- Deployment Oversight: Drive deployment strategy and oversee pod execution end-to-end. Set guardrails, governance frameworks, and quality standards across the full engagement lifecycle
- Adoption & Consumption: Own adoption, consumption, and expansion metrics post-deployment. Proactively identify blockers to consumption and develop strategies to drive measurable value realization
- Pod Leadership: Orchestrate the Builder pod, partnering closely with Technical Builders to align strategy and execution. Define scope, entry/exit criteria, and success metrics for each engagement
- AI-Powered Development: You'll be developing real customer solutions with the best-in-class suite of leading-edge AI tools: Including Cursor, Claude, and our coding products like Vibes, to accelerate development.
- Executive Stakeholder Management: Serve as the primary customer-facing contact, building trust-based relationships with C-suite executives and key stakeholders. Present strategic proposals and outcomes that demonstrate measurable impact
- Organisational 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 Agentforce platform roadmap
Requirements
- Bachelors Degree in Computer Science or related.
- 6+ years experience in strategic solutioning, technical advisory, or delivery leadership for enterprise cloud technology
- Demonstrated understanding of the Salesforce platform and ecosystem, including Agentforce and Data Cloud
- Proficiency in 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
- Exceptional communication and stakeholder management skills - ability to engage C-suite executives and translate complex technical concepts into business value
- Entrepreneurial mindset - comfortable operating in unstructured environments with a strong bias for action and outcomes
- Ability to travel 25% of the time to customer sites
Preferred Experience
- 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, etc.
- Background in change management, organisational design, or enterprise transformation
- Experience with AI/ML concepts beyond LLMs, including NLP, RAG architectures, and model evaluation frameworks