Description
About Salesforce Ventures
Salesforce Ventures is one of the most active technology investors in the world, investing across the software and AI ecosystem. Our current portfolio includes Anthropic, ElevenLabs, Physical Intelligence, Crusoe, Lovable, and hundreds of other leading companies spanning over 15 years of investing. We partner with exceptional founders at the frontier of technology and utilize the power of Salesforce's ecosystem to help them scale.
About the Role
You will be an technical analyst embedded inside a top-tier venture capital team — helping to improve the internal systems, data infrastructure, and AI-powered workflows that make a lean investment team move fast and make better decisions. You will also apply your technical expertise to deal processes by contributing to technical diligence and data-driven research that informs investment decisions.
This is not a traditional engineering role. You are joining as a technologist who builds useful systems, navigates a complex technical environment, and solves real problems for a fast-moving team — with the added dimension of learning the venture business from the inside and applying your technical judgment to how we evaluate companies and markets.
Responsibilities
Design and build internal tools and applications — deal tracking, portfolio analytics, sourcing workflows, pipeline management, and ad-hoc data requests across investment, finance, marketing, and portfolio development teams.
Build and improve data pipelines and reporting infrastructure powering essential firm activities like portfolio reviews, deployment analysis, fund performance measurement, and pipeline analytics.
Build and maintain custom integrations — MCP servers, Slack apps, and other connectors — that tie together the tools ecosystem and give AI systems deep access to internal data.
Help own Salesforce CRM data architecture: object model design, field logic, automation rules, validation, and data quality enforcement.
Ideate, build, and deploy AI-powered automations that eliminate manual work across the investment lifecycle: email processing and triage, automated company tagging, meeting brief generation, and portfolio onboarding workflows.
Build reusable AI skills, prompt pipelines, and project configurations tailored to investment workflows: sourcing, diligence, competitive analysis, and investment committee preparation.
Help conduct technical diligence on active deals — product architecture, API design, developer experience, infrastructure choices, open-source positioning, scalability, and technical moats.
Contribute to deal memos, IC question responses, and technical appendices — translating engineering assessment into investment language.
Design and lead periodic AI enablement sessions for the team — workflow demos, hands-on building time, and best practices.
Evaluate new AI/ML tools for internal usage and support data quality across all connected systems.
Requirements
Strong programming ability in Python and SQL. Tools like Claude Code have fundamentally changed how we write software, and we encourage our team to use them. But AI-driven coding places increased emphasis on engineering judgment. You are accountable for the architecture of what gets built, the quality of what gets shipped, and the maintainability of what other people depend on.
Experience building data products or internal tools. You understand how to build something that is useful to downstream users.
Comfortable with infrastructure. You've worked with cloud services (we're mostly on AWS) and IaC tools (Terraform). You can navigate working in a complex technical environment.
Experience with or strong interest in AI/LLM systems. We work with the technology we invest in.
Strong written communication. You can take messy technical and market research and synthesize it into a clear, concise communication. You can distill complex technical topics into meaningful investment insight.
Genuine curiosity about technology markets. You follow AI, security, developer tools, infrastructure, or frontier tech because you're interested. You have opinions about products and companies.
Preferred
Experience with Salesforce CRM. Familiarity with ETL/ELT tools (Fivetran, dbt). Experience with Terraform for infrastructure management. Background in venture capital, growth equity, or startup operations. Contributions to open-source projects or a public portfolio of technical work. CS, engineering, or data science degree — or equivalent self-taught depth. Experience with SaaS metrics, software business models, and/or venture finance.
The Ideal Candidate
You are a curious engineer who is excited for a generalist role. You get excited about building a tool for internal productivity and about reading a technical architecture doc for a Series B infrastructure company. You see a messy spreadsheet and instinctively think about the data model and the pipeline, not just the analysis. You are also comfortable navigating the realities of working inside a large enterprise — you understand that building at Salesforce Ventures means operating within Salesforce's security reviews, procurement cycles, and approval processes while keeping a lean investment team moving at venture speed. You know when to push, when to be patient, and how to get things done across both environments. You want to understand how venture capital works from the inside — and you see building technology as the highest-leverage way to contribute to an investment team.
Why This Role
Immediate impact for a leading technology investor. The tools and infrastructure you build will be used daily by the investment team. This is not a side project or an innovation lab; your work helps runs the operation.
Technical depth meets investment exposure. You will help evaluate the architectures of some of the most important companies in AI, security, and infrastructure. Your technical judgment will help inform investment decisions.
AI-native from day one. You will build with Claude, MCP servers, custom AI agents, and novel LLM workflows.
Unusual growth trajectory. This role develops a rare combination of engineering skill and business acumen. Few roles give you this kind of surface area across the startup and venture ecosystem — and however your career develops from here, that foundation tends to matter. The ecosystem fluency you build here opens doors that are otherwise hard to reach.
For roles in San Francisco and Los Angeles: Pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, Salesforce will consider for employment qualified applicants with arrest and conviction records.