Director, AI and Innovation

Job description

To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts. Job Category Customer Success Job Details About Salesforce Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn’t a buzzword — it’s a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all. Ready to level-up your career at the company leading workforce transformation in the agentic era? You’re in the right place! Agentforce is the future of AI, and you are the future of Salesforce. Director, AI and Innovation About the Role The Director, AI and Innovation leads the strategy, development, and adoption of artificial intelligence and emerging technology initiatives across the organization. This role partners with business, technology, and delivery leaders to identify high-impact AI opportunities, build innovation pipelines, and drive measurable business value through responsible AI adoption. Key Responsibilities • Define and drive the AI and Innovation strategy in alignment with overall business objectives. • Identify, evaluate, and prioritize AI/emerging tech use cases across the enterprise. • Lead cross-functional teams to design, pilot, and scale AI-powered solutions. • Partner with engineering, data science, and product teams to operationalize AI models responsibly. • Establish governance frameworks for responsible and ethical AI use. • Track industry trends and emerging technologies (Generative AI, Agentic AI, ML, automation) to inform roadmap decisions. • Build and manage relationships with internal stakeholders and external partners/vendors. • Present innovation roadmaps and business cases to executive leadership. • Mentor and grow a team focused on innovation and applied AI delivery. • Measure and report on ROI and adoption metrics for AI initiatives. What You Will Do (Core Responsibilities)1. Build and Own the Agent Ecosystem • Design and build a set of AI agents (scoping, estimation, risk, etc.) • Ensure they work together as a single system • Continuously improve based on real deal and delivery data. 2. Design End-to-End Workflows • Define how agents interact across the lifecycle • Ensure smooth hand-offs between agents and humans • Reduce manual steps and rework 3. Turn Business Logic into Automation • Convert scoping rules, estimation models, and governance policies into working tools • Ensure outputs are consistent, accurate, and easy to use by the field 4. Build Data & Feedback Loops • Connect delivery data into centralized data source (e.g. Data Cloud) • Track: Estimate vs actual and Margin vs plan • Use this data to improve agents over time 5. Automate Governance • Build tools that automatically check estimates against standards • Flag risks early • Enforce approval rules 6. Work Closely with Field and GDC Teams • Partner with consultants to understand real challenges • Work with Global Delivery Centers (GDC) based team to build and scale solutions • Ensure tools are practical and adopted globally 7. Partner with Salesforce Product & Engineering • Use latest platform capabilities (e.g. Agentforce, Data Cloud) • Provide feedback to improve platform features • Ensure internal tools stay aligned with product roadmap Required Qualifications • 15+ years of experience in technology strategy, innovation, or AI/ML delivery, with 5+ years in a leadership role. • Strong understanding of AI/ML concepts, Generative AI, and enterprise technology architecture. • Proven track record of leading cross-functional innovation programs. • Excellent stakeholder management, communication, and executive presentation skills. • Experience with change management and driving adoption of new technologies at scale. Strategic And Technical Expertise And ExperienceHands on experience with Large Language Models, agentic frameworks, ML Ops, and traditional AI and ML. • Proven history of delivering large programs in the AI space, including integration of operational systems, APIs, and batch/streaming pipelines. • Deep understanding of AI system governance and security, including data privacy, model integrity, observability and cost management. • Proficient in cloud technologies and enterprise-grade AI/ML platforms (e.g., AWS Sagemaker, Bedrock, Agentic, Anthropic, OpenAI, Azure ML, Databricks). • Expertise in LLMs, including fine-tuning, RAG, prompt engineering, multi-agent collaboration, orchestration frameworks, and alignment techniques. Dem