FlowGen Labs is a frontier enterprise AI company building the zero-touch enterprise: context-aware agents that operate inside deeply customized SAP environments at machine speed, grounded in each company’s ontology, current operational data, and operating procedures so complex workflows can run autonomously instead of relying on manual support teams. FlowGen is focused on turning legacy ERP from a system of record into an execution layer for finance and operations. Deployed at Fortune 500 companies across CPG, distribution, high-tech, and oil and gas, FlowGen Labs brings together a frontier AI and SAP team from DeepMind, SAP, Meta AI, and Amazon AGI Labs.
Role SummaryBuild the systems that help FlowGen find the right customers and turn interest into revenue. You will work directly with the founders and go-to-market team to connect data, software, and AI across prospecting, marketing, and sales, giving a small team the reach and execution speed of a much larger one.
This is a hands-on engineering role with broad ownership. You will identify the real constraint, build a practical solution, and remain accountable through deployment, adoption, and measurable results. You will:
Build automated workflows that turn customer signals into qualified pipeline: account discovery, enrichment, prioritization, lead routing, and outbound activation.
Own enrichment end to end. Turn inbound interest, target account lists, and event contacts into accurate, deduplicated CRM records with useful account context and clear next steps.
Develop account scoring around our ideal customer profile. Combine company data, buying signals, and AI research to help the team focus on enterprises where FlowGen can deliver the most value.
Build AI agents and internal tools for account research, meeting preparation, call summaries, proposals, and RFP or security questionnaire drafts. Put useful account intelligence into the team's daily workflow.
Connect our CRM, enrichment providers, outbound tools, and internal data systems through APIs and reliable data pipelines. Own the data models, sync logic, and quality of the information the team relies on.
Ship code that holds up in production: clear reviews, logging, monitoring, retries, and error handling. Debug broken integrations, failed data jobs, and unreliable model outputs, and fix the underlying cause.
Work with the founders and sales team to find repetitive work, test new approaches, and measure what improves pipeline quality, conversion, and time spent selling. Keep improving the systems as the company scales.
1+ years building software or technical systems in GTM engineering, growth engineering, revenue operations, sales engineering, or a closely related role. A track record of shipping useful systems matters more than a specific title.
Strong Python and TypeScript skills. You can work with APIs and asynchronous workflows, design a database schema, and debug a production issue from logs.
Hands-on experience with a modern GTM stack: CRMs, enrichment tools, and outbound platforms. You understand how accounts and leads move through a sales process and how to keep the underlying data trustworthy.
Practical experience building with LLMs, including prompt design, evaluations, structured outputs, and handling failures. You know how to make an AI workflow dependable enough for people to use every day.
Strong SQL skills and sound judgment about data models, integrations, and pipeline design. You think through duplicate records, API limits, concurrent updates, and what changes when volume grows.
Strong business judgment and crisp communication. You can turn an ambiguous sales or marketing problem into a scoped project, explain the tradeoffs, and connect technical work to business outcomes.
Ownership mentality and follow-through on the details. No job is too small: you'll build a new agent and fix the broken CRM sync, and you do both well.
Real curiosity about enterprise AI, agentic workflows, and how large companies actually operate. Experience building CRM integrations or production AI applications is especially useful.
Work directly with the founders and shape how an early-stage frontier enterprise AI company scales.
Help define how autonomous agents operate inside the systems that run the world’s largest companies.
Direct product and company impact with minimal bureaucracy.
A high bar for craft, velocity, accountability, and pragmatic shipping.
Location: In person, San Francisco Bay Area
Employment: Full time
Total Compensation: $150,000–$250,000 per year, including base salary and equity. The final package will depend on experience and scope.
Visa support and sponsorship available
Skills Required
- 1+ years building software or technical systems in GTM engineering, growth engineering, revenue operations, sales engineering, or a related role
- Strong Python skills
- Strong TypeScript skills
- Experience working with APIs and asynchronous workflows
- Ability to design database schemas and debug production issues using logs
- Hands-on experience with modern GTM stacks, including CRMs, enrichment tools, and outbound platforms
- Practical experience building with LLMs, including prompt design, evaluations, structured outputs, and failure handling
- Strong SQL skills
- Sound judgment regarding data models, integrations, and pipeline design
- Strong business judgment and clear communication
- Ownership mentality and strong follow-through
- Curiosity about enterprise AI, agentic workflows, and large-company operations
- Experience building CRM integrations or production AI applications
What We Do
Agentic Operating Procedures for your ERP. Execute at machine speed, learn from every exception, and improve with every transaction.
