Salesforce

Solutions Engineer

• A Solution Engineer plays a pivotal role in aligning innovative strategies to technology solutions within complex accounts.
• This role focuses on partnering with clients and collaborating with internal team members and C-level client contacts to drive consensus on multi-product technology solutions across the various Salesforce product lines.
• Solutions Engineers work on a wide array of assignments including business development, operations and IT strategies, as well as executive level product demonstrations.
• This person must assume the role of trusted advisor for driving innovative solutions forward while also improving business performance.

Solution Engineer – Pre-Sales, All Levels

Machine Learning Engineer

• Design and execute finetuning strategies for large language models and other deep learning architectures tailored to Slack's NLP tasks
• Own the model training lifecycle end-to-end: data curation, training infrastructure, hyperparameter optimization, evaluation, deployment and monitoring
• Build and maintain scalable finetuning training pipelines on GPU infrastructure
• Brainstorm with Product Managers, Designers and Frontend Engineers to conceptualize and build new features
• Produce high-quality results by leading or contributing heavily to large multi-functional projects
• Mentor other engineers and deeply review code
• Improve engineering standards, tooling, and processes

Staff ML Engineer, Fine Tuning

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

Procurement

• Partner with key stakeholders and Chief Procurement Officer to develop and implement a comprehensive procurement strategy.
• Continuously assess and adjust the strategy to respond to market dynamics and industry trends.
• Build and maintain strategic relationships with key suppliers.
• Negotiate and manage supplier contracts, pricing, and performance.
• Drive agentic transformation and process streamlining in Sourcing & Procurement organizations
• Identify opportunities for cost reduction and efficiency improvements.
• Collaborate with cross-functional teams to improve supply chain visibility, flexibility, and responsiveness.
• Lead and develop a high-performing procurement team, fostering a culture of excellence.

Vice President, Technology Sourcing – Procurement

• Understand customer goals and challenges and map those back to the Salesforce product portfolio
• A skillset to establish trust with clients, and the ability to influence key decision makers
• Hands-on Java development experience and ability to code and debug against Java APIs is preferred
• Experience with cloud technologies - iPaaS, SaaS applications, cloud infrastructure, etc. is preferred
• Participate in all appropriate product, sales, technical training and certifications to acquire and maintain the knowledge necessary to be effective in the position
• Attain quarterly and annual objectives defined collaboratively with management
• Respond effectively to RFIs/RFPs
• Active participation in a fast-paced high-energy market segment and balance multiple projects in a team-selling environment

Solution Engineer, MuleSoft

Architect

• Be a trusted Agentforce + Data Cloud subject-matter expert for the broader Success Architect organization, including how Data Cloud relates to the success of AI
• Engage with our Signature and Strategic customers to evaluate and recommend optimization strategies for technical architecture, dev/ops, performance, and solution design specific to Agentforce + Data Cloud
• Identify and evaluate capability gaps for standard product capability or identify creative Architect solutions through customization
• Facilitate and influence Executive stakeholders while aligning technology strategy to business value and ROI
• Run playbooks aligned with our Success Architect engagement catalog, tailored to the unique needs and opportunities of Agentforce + Data Cloud customers
• Build strong relationships with both internal and external business partners, contributing to broader goals and growth
• Drive thought leadership through mentoring and knowledge sharing

Data 360 Success Architect

• Align innovative strategies to technology solutions within complex accounts
• Partner with clients and collaborate with internal team members
• Drive consensus on multi-product technology solutions across Salesforce product lines
• Solve ambiguous and sophisticated business problems
• Convey a deep understanding of the customer's enterprise architecture
• Develop technical Points of View (POVs) on AI strategy
• Demonstrate through software demos and rapid prototyping
• Lead cross-functional solutions guides and share best practices

Account Solution Engineer – Payer

AI Engineer

• Partner closely with Marketing strategy, operations, and creative leads to surface highest-impact, repeatable workflows
• Design comprehensive end-to-end workflow architectures
• Architect and build scalable, reliable AI agents that execute full marketing workflows
• Design and implement distributed systems that securely integrate with Marketing’s existing tools
• Define and instrument success metrics for every agent
• Maintain and evolve a shared system context repository
• Communicate technical trade-offs and architectural decisions clearly to non-technical Marketing leadership

Principal AI Engineer

• Promote Salesforce Field Service and Salesforce Scheduler value propositions to customers (including C-level executives and IT) and field teams
• Evaluate business operations and technology impact assessments
• Present comprehensive findings including critical pain points, proposed solutions aligned with business requirements, and return on investment analysis where applicable
• Contribute to the development of technical sales strategies
• Configure and demonstrate innovative solutions that accurately reflect each customer's unique business requirements through customized presentations
• Analyze and recommend optimal solution architectures
• Partner with Field Sales teams, Account Executives, and Product Management to deliver appropriate solutions while establishing credibility and trust with customers

Lead Solution Engineer, Field Service

Account Executive

• Cultivate and maintain enduring relationships with State Gov clients
• Utilize data analysis to pinpoint areas for improvement and make data-driven recommendations.
• Provide regular progress updates to management regarding client accounts.
• Monitor and report on key performance metrics, including client retention and revenue growth.
• Maintain a high level of client satisfaction by consistently exceeding expectations.
• Work collaboratively with internal teams to devise solutions for complex challenges.
• Address and resolve client issues in a timely and efficient manner.
• Keep clients informed about new product features, updates, and enhancements relevant to their needs.
• Identify growth opportunities within existing accounts and work towards expanding Salesforce services.
• Collaborate closely with clients to formulate customized account strategies.
• Educate clients on how Salesforce can empower them to streamline operations and enhance service delivery.
• Stay informed about industry trends, government regulations, and competitive offerings.
• Develop an in-depth understanding of Salesforce products and solutions.
• Conduct regular meetings and check-ins to assess client satisfaction and identify areas for improvement.
• Act as the primary point of contact, ensuring that client inquiries and concerns are addressed promptly.

Named Account Executive, State Government

• Lead the end-to-end design, development, and scaling of the AI governance platform, building both the front-end and back-end components that support enterprise wide AI governance
• Use AI development tools such as Claude and other coding assistants as part of the software development lifecycle to accelerate delivery, improve code quality, prototype faster, and enhance engineering productivity
• Design and build secure, scalable, and resilient cloud native infrastructure on AWS to support platform services, governance workflows, system integrations, and application performance at enterprise scale
• Build and support platform capabilities that enable AI and machine learning systems to be governed, monitored, tracked, and managed throughout their lifecycle, including services that support model and agent operations
• Bring practical knowledge of CI/CD concepts, automated testing, and deployment workflows, and release management practices to help ensure the platform can be delivered reliably across environments
• Define and drive the overall platform architecture, including service design, API strategy, data flows, integration patterns, event-driven workflows, and system scalability considerations
• Develop monitoring capabilities that provide insight into system health, application performance, workflow execution, service reliability, and platform usage across the governance ecosystem
• Build observability components that capture logs, metrics, traces, and runtime telemetry across platform services, enabling deeper diagnostics, issue detection, root cause analysis, and ongoing operational intelligence
• Assist with designing and developing Generative AI capabilities as part of the platform, including LLM powered features, intelligent workflows, agent-based functionality, and other AI native applications
• Provide strong technical leadership across the stack, establish engineering standards, influence design decisions, mentor other engineers, and take ownership of delivering a strategic platform from the ground up
• Partner closely with product, architecture, security, compliance, governance, and engineering stakeholders to translate business goals and trust requirements into scalable technical solutions

Lead Engineer – AI Trust & Governance

• 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

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

Solution Engineer – Pre-Sales, All Levels

Staff ML Engineer, Fine Tuning

Software Engineer II, Service Network

Vice President, Technology Sourcing – Procurement

Solution Engineer, MuleSoft

Data 360 Success Architect

Account Solution Engineer – Payer

Principal AI Engineer

Lead Solution Engineer, Field Service

Named Account Executive, State Government

Lead Engineer – AI Trust & Governance

Principal AI Engineer

Software Engineer II – Service Network

Senior Member of Technical Staff – AI Research

Senior Product Manager, Customer Health Platform