GTM Engineer

Description

The company is an enterprise AI company building context-aware agents that run inside heavily customized SAP environments at machine speed, so complex workflows can operate autonomously rather than depending on manual support teams. The agents are grounded in each customer's ontology, live operational data, and operating procedures.

The company is turning legacy ERP from a system of record into an execution layer for finance and operations. Its product is deployed at Fortune 500 companies in CPG, distribution, high-tech, and oil and gas. The team combines frontier AI and SAP experience from DeepMind, SAP, Meta AI, and Amazon AGI Labs.

The role is a go-to-market engineering position that builds the systems used to find the right customers and convert interest into revenue. You will work directly with the founders and the go-to-market team, linking data, software, and AI across prospecting, marketing, and sales so a small team can reach and execute like a much larger one.

You will own problems from diagnosis through deployment, adoption, and measured results, building practical solutions as you go.

Responsibilities

• Build automated workflows that convert customer signals into qualified pipeline, covering account discovery, enrichment, prioritization, lead routing, and outbound activation.
• Own enrichment from start to finish, turning inbound interest, target account lists, and event contacts into accurate, deduplicated CRM records with useful account context and clear next steps.
• Create account scoring based on the ideal customer profile, combining company data, buying signals, and AI-driven research to show the team where FlowGen can add the most value.
• Build AI agents and internal tools for account research, meeting prep, call summaries, proposals, and drafts of RFP and security questionnaire responses, and get useful account intelligence into the team's daily routine.
• Connect the CRM, enrichment providers, outbound tools, and internal data systems through APIs and dependable data pipelines. Own the data models, sync logic, and the quality of the information the team depends on.
• Ship production-grade code with thorough reviews, logging, monitoring, retries, and error handling. Investigate broken integrations, failed data jobs, and unreliable model outputs, and fix the root cause.
• Work with the founders and sales team to find repetitive work, test new approaches, and measure gains in pipeline quality, conversion, and selling time. Keep evolving the systems as the company grows.

Requirements

• At least 1 year of experience building software or technical systems in GTM engineering, growth engineering, revenue operations, sales engineering, or a closely related role. A record of shipping useful systems counts more than a particular job title.
• Strong Python and TypeScript. You can work with APIs and asynchronous workflows, design a database schema, and trace a production issue through logs.
• Hands-on experience with a modern go-to-market stack, including CRMs, enrichment tools, and outbound platforms. You understand how accounts and leads move through a sales process and how to keep the data reliable.
• Practical experience building with LLMs, including prompt design, evaluations, structured outputs, and failure handling. You can make an AI workflow dependable enough for daily use.
• Strong SQL and sound judgment on data models, integrations, and pipeline design. You account for duplicate records, API rate limits, concurrent updates, and how things change as volume grows.
• Strong business judgment and clear communication. You can turn a vague sales or marketing problem into a scoped project, explain tradeoffs, and tie technical work to business results.
• An ownership mindset and attention to detail. No task is too small: you will build a new agent and fix a broken CRM sync with equal care.
• Genuine interest in enterprise AI, agentic workflows, and how large companies operate. Experience with CRM integrations or production AI applications is especially useful.

Conditions

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 depends on experience and scope.

Visa support and sponsorship are available.

The company is an equal opportunity employer.

Benefits

• Work directly with the founders and help shape how an early-stage enterprise AI company scales.
• Help define how autonomous agents operate inside the systems that run some of the largest companies in the world.
• Direct impact on product and company with minimal bureaucracy.
• A high standard for craft, speed, accountability, and practical shipping.