Research & Field Validation Deploy and stress-test pilot CCaaS features with customers, identifying platform gaps and feeding structured findings back to Technology & Product
Conduct feasibility research on novel use cases — determining what's possible, what's not, and what needs to change in the product to get there
Co-develop hypotheses with Technology & Product and design experiments to validate them in the field
Document and escalate critical engineering issues with detailed evidence packages to accelerate resolution
Lead technical engagement of new Agentforce CCaaS solutions — including Voice Agent deployments, SIP/telephony integration, intelligent routing, post-call automation, and omnichannel orchestration
Embed directly with customer teams to deeply understand their operational environment and architect solutions that solve real problems at scale
Run rapid prototyping and POC cycles to validate technical feasibility
Serve as the primary technical advisor and escalation point for your customer portfolio
Build reusable accelerators, playbooks, and reference architectures that address critical product gaps and directly shape the agentic platform roadmap
Partner directly with Product Managers and Engineers to influence roadmap priorities based on evidence captured directly from customers
Represent the voice of the customer in internal product discussions and planning cycles
Analyze competitive landscape to identify and validate Salesforce's key differentiators — informing both field engagements and product feedback loops
Produce thought leadership, best practices, and enablement content that raises the bar for new product releases across the Salesforce community
Requirements
7+ years of hands-on engagement in enterprise software or SaaS environments, with a strong foundation in Computer Science, Engineering, or a related discipline
Expertise in enterprise CCaaS concepts: Voice & Digital Channel Management, IVR/IVA Design, Intelligent Routing, Workforce Management, and Omnichannel Orchestration
Hands-on experience with SIP/VoIP protocols, telephony infrastructure, and CTI integrations
Demonstrated experience deploying AI/LLM-based solutions — including agentic frameworks, prompt engineering, and retrieval-augmented generation (RAG)
Deep expertise in enterprise data architecture, security, and integrations, including REST/GraphQL APIs, SaaS platform architecture, and common data integration patterns
Proficiency in one or more programming languages (Python, JavaScript, Apex, or Java)
Strong diagnostic and problem decomposition instincts — able to pinpoint whether a failure is a product bug, a configuration error, or a data issue, even in low-documentation environments
Exceptional written communication skills: able to document builds, failures, and field observations in structured form that Product & Engineering can act on without a follow-up call
Experience with product telemetry and observability analysis to identify platform patterns and surface actionable insights
High agency, self-motivation, and agility quotient — you thrive in ambiguous, high-stakes environments, operate without a playbook, and default to experimentation and fast iteration over certainty, treating every challenge as an opportunity to learn and evolve
Ability to travel 20–30% to customer sites and company engagements