Salesforce

AI Engineer

• Design and build agent harness infrastructure: the scaffolding that wraps LLM calls, manages tool use, handles retries, enforces policy, and feeds results back into iterative improvement loops.
• Implement agentic loop patterns with multi-turn reasoning, tool orchestration, memory management, and structured output handling as reusable platform primitives
• Build the agent flywheel: automated pipelines that collect agent traces, surface regressions, route failures to evaluation, and close the loop from production signal back to prompt/model improvement
• Own the end-to-end lifecycle from agent experiment to production deployment, including versioning, rollout controls, and rollback mechanisms
• Build sandboxed execution environments for agent tools with isolating code execution, API calls, and file system access so agents can act without unconstrained blast radius
• Design tiered autonomy models: define which actions agents can take automatically, which require human approval, and which are off-limits and enforced at the infrastructure layer
• Implement replay and dry-run capabilities so new agent versions can be tested against real traces before going live
• Implement evaluation frameworks for agent behavior using a combination of vendor, open source or in house built tools — covering task success, tool selection accuracy, trajectory evaluation, hallucination rates, latency, and cost
• Build and maintain eval datasets, golden trace libraries, and regression test suites that run automatically on every agent code change
• Instrument agent traces end-to-end: LLM calls, tool invocations, intermediate reasoning, final outputs — surfaced in Grafana or equivalent observability tooling
• Define and track agent quality metrics over time; own the signal that tells the team whether agents are getting better or worse
• Drive continuous quality, latency, and cost improvements across deployed agents by closing the loop between production traces, evaluations, and agent design. Optimization may be done through a variety of techniques e.g. prompt tuning, tool calling optimizations, context engineering, right-sizing model selection per task and explore distillation or fine-tuning (SFT, DPO, RLHF) on curated trace data to name a few
• Validate every optimization through A/B tests, shadow deployments, and replay against golden traces, with the eval suite gating rollout so wins are real and regressions are caught before they reach users
• Build and optimize CI/CD pipelines (GitHub Actions, ArgoCD) that cover not just code deployment but agent evaluation gates — no agent ships without passing its eval suite
• Automate Docker and package builds, security scanning, and agent integration tests as first-class pipeline steps
• Design self-healing CI patterns where agent-based automation can diagnose and fix common pipeline failures
• Build internal tools and developer self-service interfaces that let ML engineers and data scientists iterate on agents without platform team involvement
• Maintain a comprehensive view of how all platform components -> infrastructure, agent harnesses, evaluation pipelines, observability — work together
• Create architecture diagrams and drive long-term platform vision; own the "how does this scale to 10x" conversation
• Establish alerting (Grafana, PagerDuty) for both traditional platform health and agent-specific signals (error rates, tool call failures, eval score drift)
• Ensure all agent infrastructure adheres to security best practices: sandboxed execution, auditable traces, access controls on every tool
• Participate in security reviews; own compliance for agent workloads

Principal AI Engineer

Full-stack Engineer

• Contribute to the design, development, and operation of scalable, reliable, and secure service mesh infrastructure that enables service-to-service communication across the platform.
• Implement and support service mesh capabilities including service discovery, observability, traffic routing, and security features such as mTLS and policy enforcement.
• Assist in troubleshooting production issues across distributed systems, Kubernetes environments, networking, and Linux-based infrastructure.
• Participate in improving platform reliability, performance, and operational efficiency through automation and tooling.
• Contribute enhancements and fixes to internal tooling and, where appropriate, open-source technologies such as Envoy.
• Support incident response and operational excellence efforts to help maintain platform availability and service-level objectives (SLOs).
• Stay current with emerging cloud-native and service mesh technologies and apply best practices to improve the platform.

Software Engineer II – Service Network

AI Research Scientist

• design, implement and iterate agentic AI systems with customers
• innovate at the frontier of the field
• create new solutions and define new categories of product with meaningful impact to Salesforce customers
• build and maintain the shared system context that enables AI to operate accurately and reliably

Senior Member of Technical Staff – AI Research

Product Manager

• Own product strategy, roadmap, and end-to-end delivery for across multiple scrum teams and an AI research team
• Define and evangelize the product vision
• Develop and maintain a comprehensive roadmap
• Identify and address key customer pain points
• Translate high-level business requirements into detailed product specifications
• Collaborate with engineering and UX teams to build scalable, intuitive, and high-impact solutions
• Lead cross-functional teams through the product development lifecycle
• Engage directly with customers, partners, and stakeholders to deeply understand pain points
• Drive prioritization and trade-offs across user experience, performance, and technical feasibility
• Leverage data-driven insights to iterate and improve product offerings
• Partner with sales, marketing, and enablement teams to ensure successful product launches and adoption
• Stay ahead of industry trends in AI, collaboration, automation, and enterprise service management
• Serve as the voice of the customer

Senior Product Manager, Customer Health Platform

Artificial Intelligence

• Help the SVP translate high-level strategy into execution-ready alignment across multiple product lines, turning ambiguity into order.
• Actively look across product teams to identify gaps and friction points in AI functionality, identity, security, data architecture, and platform APIs.
• Lead product reviews and governance processes to surface and resolve ecosystem conflicts before they impact customers.
• Build and maintain a living map of portfolio capabilities, overlaps, gaps, and interdependencies to ensure Salesforce moves as a unified AI platform.
• Serve as a trusted advisor to product GMs and business unit product leaders on the portfolio-level implications of local roadmap decisions.
• Apply program management rigor to keep matrixed alignment workstreams and stakeholder commitments on track.
• Partner with leadership to prepare portfolio coherence and AI strategy materials for executive and board-level planning conversations.
• Partner closely with pricing, finance, and product leadership to identify inconsistencies or risks in cross-portfolio packaging and AI monetization strategies.
• Champion intuitive, portfolio-level pricing logic without needing to own the direct pricing execution.
• Conduct structured capability gap assessments against market shifts and competitive AI benchmarks.
• Identify and prioritize acquisition or partnership targets that can accelerate our horizontal AI and platform capabilities.
• Lead the product-side due diligence on inbound and outbound M&A targets, ensuring seamless integration potential.

Senior Director – Portfolio Product Strategy, AI Alignment

Account Executive

• As a Data Foundation AE, you own both MuleSoft and Informatica as part of your portfolio
• You carry quota for both MuleSoft and Informatica - covering both products in full
• You lead deep-dive sessions with CIOs and Data Architects to uncover fragmented systems
• You are the 'quarterback' engaging with both MuleSoft and Informatica
• You hunt for high-value use cases across both products
• You'll prove that without a robust Data Foundation - built on MuleSoft and Informatica - an enterprise's AI and Data investments cannot succeed

Enterprise Account Executive – Data Foundation

Engineer

• Own the roadmap for process blueprints and automation solutions, balancing strategic direction with foundational execution needs
• Own the feature lifecycle for specific components from discovery through launch and iteration
• Identify operational inefficiencies, manual processes, and automation opportunities across customer and internal workflows
• Partner with customer-facing team leaders to map and analyze customer requirements for new solutions
• Build solution blueprints and workflow automations using current platform features
• Work directly with AI agents and prompting tools to design automated, enterprise-grade solutions
• Validate, test, and iterate blueprints for accuracy, consistency, and performance
• Translate high-level strategic goals and customer requirements into clear Product Requirement Documents (PRDs), user stories, and technical acceptance criteria
• Manage the product backlog, prioritize sprints, and drive consistent delivery using Agile methodologies
• Document solution architecture, demonstrations, and implementation guidelines
• Conduct user interviews and quantitative analysis to deeply understand customer pain points and identify product opportunities
• Act as the voice of the customer within the development process
• Partner with Engineering and Design (UX/UI) to ensure technical feasibility and intuitive user experiences
• Provide structured, detailed feedback to Product Managers regarding feature gaps and enhancements needed to support scalability
• Support rollout and enablement of blueprint solutions across teams and customers

Forward Deployed Engineer

Manager

• Act as a trusted strategic partner to AVP Sales leaders for the Platform OU, embedding yourself in the business to understand priorities, challenges, and performance drivers.
• Diagnose business needs using both qualitative insight and quantitative analysis, proactively identifying opportunities where enablement and sales programs can improve productivity, pipeline generation, and execution.
• Bring a point of view to leadership conversations, influencing decisions through data, insight, and thoughtful recommendations.
• Understand and translate global enablement and sales programs initiatives into targeted, high-quality execution for the Platform OU, ensuring relevance, clarity, and strong adoption.
• Design and deliver OU-specific enablement and sales programs initiatives that address market maturity and seller needs, while staying aligned to broader business priorities.
• Balance strategic thinking with hands-on execution, ensuring enablement and sales programs are delivered with consistency, quality, and measurable impact.
• Support seller productivity across the full lifecycle, with particular focus on accelerating new hire ramp and early productivity.
• Partner on onboarding experiences and reinforcement strategies to ensure sellers are enabled to succeed quickly and sustainably.
• Identify best practices and scale learnings across OUs and the wider INTL organization where appropriate.
• Collaborate closely with distribution, marketing and other operational teams (Strategy & Global Sales Programs) to deliver cohesive, end-to-end enablement solutions.
• Act as a connector across functions, aligning efforts to ensure sellers receive clear, consistent messaging and support.
• Define success metrics for enablement initiatives and leverage data to assess impact on productivity, ramp, and business performance.
• Use insights and feedback from the field to iterate, improve, and evolve enablement approaches over time. Stay curious and innovative, continuously exploring new ways to improve enablement effectiveness in a rapidly changing environment.

Enablement Manager

Recruitment

• Act as a trusted partner to Recruiting leadership and cross-functional teams.
• Represent the recruiting function in large-scale projects, influence decision-making, and provide SME-level guidance on recruiting operations, tools, and workflows.
• Own and continuously improve components of our recruiting technology stack (ATS, scheduling platforms, assessments, etc.) by identifying gaps, evaluating processes, and creating impact in partnership with systems teams.
• Lead process improvement initiatives focused on scalability, automation, and simplification.
• Leverage recruiting and operational data to identify trends, monitor performance, and develop actionable insights.
• Support the planning and execution of recruiting programs and technology implementations.
• Oversee the development and governance of process documentation, training materials, and self-serve knowledge resources.
• Partner with Recruiting Enablement to manage logistics for in-person and virtual events.

Recruiting Operations Manager

• Design and develop highly scalable and resilient streaming and batch pipelines for ingesting and processing structured and unstructured datasets
• Design and implement Slack’s Lakehouse solutions and enable production use cases for customers
• Improve the reliability and performance of the services/pipelines through AI assisted and/or Agentic solutions and tools.
• Automate and handle the lifecycle of datasets (schema evolution, metadata management, change and backfill management, deprecation and migration).
• Collaborate with cross functional partners and lead technical initiatives independently end to end.
• Write, review, or provide feedback on a technical design proposal from others.

Staff Software Engineer, Data Ingestion

Customer Success Manager

• leading a team of customer success professionals
• developing the strategy and tactics to leverage your team
• advocating for customers by driving alignment across various departments
• building and developing a world-class team
• sponsoring customers throughout their journey
• ensuring your team delivers on high growth targets and key performance metrics
• personally engaging with top prospects

Senior Manager, Customer Success Management

Marketing

• Define and lead the global SMB growth strategy across Salesforce’s product portfolio
• Own the business outcomes for SMB acquisition, pipeline generation, conversion efficiency, retention, and expansion
• Build and operate a modern global SMB growth engine spanning paid, owned, lifecycle, web, SEO, social, content, partner, and event channels
• Drive full-funnel performance with rigorous accountability around CAC, LTV, pipeline efficiency, conversion, and ROI
• Partner deeply with Product & Engineering to shape customer journeys, onboarding experiences, activation models, and product-led growth motions
• Build strong operational trust and alignment with Sales leadership around pipeline quality, velocity, and revenue performance
• Lead integrated global campaigns and growth programs designed to scale customer demand and brand relevance in the SMB segment
• Create a high-velocity experimentation culture using AI and agents, automation, data science, and agentic systems to continuously optimize growth
• Build a world-class operating cadence grounded in data, accountability, execution excellence, and speed
• Lead and scale a high-performing global team across multiple functions and geographies
• Help define the future of AI-powered SMB growth at Salesforce

SVP, Global SMB Marketing

Growth Marketing

• Define and lead the vision and operating strategy for Global Growth Systems across Salesforce
• Build Salesforce’s next-generation intelligent growth engine spanning digital engagement, lifecycle orchestration, AI, automation, experimentation, and customer intelligence
• Transition marketing from static, campaign-based execution to an adaptive, always-on growth system
• Architect unified customer engagement systems across paid, owned, web, lifecycle, SEO/SEM, social, and emerging AI-driven channels
• Design intelligent decisioning systems that continuously optimize acquisition, conversion, retention, and expansion in real time
• Lead the adoption and integration of AI, automation, and agentic technologies across the global marketing ecosystem
• Partner deeply with Product & Engineering to build scalable growth infrastructure, customer experiences, experimentation systems, and AI-powered workflows
• Create an operational culture grounded in experimentation, speed, accountability, data, and measurable business outcomes
• Drive organizational transformation, capability building, and operating model evolution across people, process, and technology
• Build and lead a world-class global organization spanning growth, marketing technology, AI, analytics, automation, and digital strategy
• Establish Salesforce as an industry leader in AI-powered enterprise growth systems

SVP, Global Growth Systems

Backend Engineer

• Prototype quickly to validate ideas, expose platform gaps, and unblock first-of-kind implementation risks.
• Build reference implementations, starter kits, demos, field kits, and evaluation harnesses that partners can fork, extend, and deploy.
• Convert field lessons into durable reusable assets: code, diagrams, checklists, decision trees, implementation notes, and architecture guidance.
• Review partner Agentforce architectures for agent design, retrieval strategy, tooling, guardrails, observability, cost, security, and production readiness.
• Coach Partner FDEs and architects through design clinics, office hours, portfolio reviews, and targeted technical walkthroughs.
• Translate recurring field blockers into clear product and engineering feedback.
• Help partners connect technical architecture choices to delivery quality, customer outcomes, and consumption economics.

Partner Technical Architect

Performance Marketing

• Own and execute the global paid search strategy across Google Ads, Microsoft Advertising, and emerging search platforms
• Build and embed AI and automation tools into daily workflows
• Partner with SEO, Web, and Product teams to align paid and organic search strategy
• Define the SEM measurement framework and communicate insights to senior leadership