Principal AI Solutions Engineer - Salesforce AI Labs

Salesforce • San Francisco, CA

3d

About The Position

Salesforce AI Labs is building a small team of hands-on technology builders to connect the capabilities of AI-native businesses and software companies into working software and compelling business stories. This senior individual-contributor role combines software engineering, applied AI, solution architecture, and storytelling. The engineer connects products, models, agents, and data into demonstrable solutions and helps customers and executives understand their value.

The role focuses on building and demonstrating how capabilities across the Salesforce AI Labs portfolio can work together to deliver measurable customer outcomes faster. It involves showing what customers can achieve with current capabilities, exploring new combinations, and explaining a clear path from current capabilities to future possibilities.

The position works with customers, portfolio leaders, and go-to-market teams to identify valuable use cases; builds prototypes, API integrations, and agent workflows across products and enterprise systems; and creates reliable, repeatable demonstrations. It also packages reusable technical assets, evaluates customer and business outcomes, and provides evidence-based feedback to product and engineering leaders. Proposed initial outcomes include understanding the portfolio and selecting customer scenarios in the first 30 days, delivering a working multi-product demonstration by 60 days, and validating and packaging the scenario for reuse by 90 days.

Requirements

• A track record of personally building customer-facing software, integrations, or technical prototypes that solve real business problems.
• Strong coding skills in Python, TypeScript/JavaScript, or comparable languages, including the ability to build and debug across services and create a usable demonstration interface.
• Fluency in modern API architectures, including authentication, webhooks, event-driven integration, data contracts, and reliable execution across systems.
• Practical experience building with models and tools from providers such as OpenAI and Anthropic, alongside relevant open-source agent frameworks and harnesses.
• Understanding of tool calling, retrieval, orchestration, context management, evaluations, observability, and human approval within agent workflows.
• Sound judgment about model limitations, reliability, latency, cost, data access, and requirements for moving from prototype to customer deployment.
• Strong storytelling and presentation skills, including delivering live demonstrations and explaining their business significance.
• Initiative to work through ambiguity, learn unfamiliar products quickly, and ship useful iterations with a small team.
• Ability to turn a broad ambition into a testable use case with a credible path to customer value.

Nice To Haves

• Experience in forward-deployed engineering, applied AI engineering, solutions engineering, or customer-facing solution architecture.
• Experience building demonstrations or proofs of value involving multiple enterprise products.
• Experience with process intelligence, workflow automation, customer research, customer service, or digital experience platforms.
• Experience creating reusable technical assets that support several customers or go-to-market teams.
• Startup or founding-engineer experience with direct customer engagement.

Responsibilities

• Build working prototypes, API integrations, and agent workflows spanning multiple products and enterprise systems.
• Work with customers, portfolio leaders, and go-to-market teams to identify use cases where combined capabilities can deliver meaningful additional value.
• Develop reliable, repeatable demonstrations that connect customer needs, system actions, and business results.
• Present to executives, customers, developers, and sales teams, adapting the level of detail while maintaining technical credibility.
• Use rapid experimentation to test new agentic experiences and architectures, distinguishing available capabilities from prototypes and future concepts.
• Package reference architectures, integration components, demo environments, and playbooks for reuse by other teams.
• Establish baselines and evaluate outcomes such as implementation time, process cycle time, cost to serve, service resolution, and customer experience.
• Share integration gaps, customer demand, and technical constraints with product and engineering leaders, supported by evidence from the work.
• In the first 30 days, understand the portfolio, map integration opportunities, and select two high-value customer scenarios with business sponsors and measurable outcomes.
• By 60 days, deliver one working demonstration across multiple products, with a clear story, documented dependencies, and an initial evaluation of reliability and value.
• By 90 days, validate a scenario with customer or field teams, package it for reuse, and propose subsequent build priorities based on evidence.

Benefits

• Time off programs
• Medical insurance
• Dental insurance
• Vision insurance
• Mental health support
• Paid parental leave
• Life insurance
• Disability insurance
• 401(k)
• Employee stock purchasing program
• Certain roles may be eligible for incentive compensation and equity

What This Job Offers

• Job Type: Full-time
• Career Level: Principal
• Education Level: No Education Listed