Job description

Finite State partners with product security teams, the guardians of our connected world, to create transparency for their connected devices and supply chains. Our platform handles connected devices and embedded systems across all industries, including those found in enterprises, healthcare, utilities, connected vehicles, manufacturing facilities, critical infrastructure, and government entities.

We are a fast-growing series-B company with a fully distributed workforce. Led by a team of seasoned experts, we are a mission-driven team passionate about arming our customers with the actionable insights, critical vulnerability data, and remediation guidance necessary to mitigate product risk and protect the connected attack surface. We are committed to a remote first culture.

Location: Remote, U.S. - based
Department: GTM Ops

The Opportunity

Agent Systems Engineer is what we call this role. You may know it as GTM Engineer, Revenue Systems Engineer, Growth Engineer, or internal Forward Deployed Engineer. The substance is the same. You’re a deeply technical operator who embeds with revenue teams, learns how the business actually moves, and rebuilds workflows as governed, AI-augmented systems.

You write SQL fluently. You live in APIs. You’ve shipped production GTM automation that other people depend on. You know what good revenue data architecture looks like (warehouse as source of truth, modeled in dbt, activated into Salesforce and the rest of the stack via Reverse ETL) and you have opinions about why most companies get it wrong.

You also believe in practical AI. You’ve deployed LLMs against real GTM problems where the business value was concrete (account research, classification, enrichment, content generation), and you have honest views about what worked, what didn’t, and where the hype outpaces reality.

Most companies treating AI as a productivity tool are pointing it at individual jobs. We think the bigger opportunity is rebuilding entire revenue processes around agents and modern data infrastructure. We sell that thesis to product security teams every day. Running our own GTM motion the same way is how we hold ourselves to the standard we’re selling.

You’d be first in seat at Finite State, so you own the full motion: discovery with revenue leaders, system design, build, governance, evaluation, rollout, and the runbook so it survives you.

Responsibilities

Run discovery with revenue leaders before building. Sit in pipeline reviews. Watch a deal cycle end-to-end. Find the actual time sinks before designing a solution
Architect the GTM data layer: Snowflake (or equivalent) as source of truth, dbt for modeling, Reverse ETL (Hightouch, Census) for activation into Salesforce, HubSpot, Outreach, and the rest of the stack
Design and build AI agents and AI-augmented workflows for revenue-critical work: account research, ICP scoring, signal-based plays, outbound personalization, CRM enrichment, deal intelligence, churn risk, expansion triggers, lead routing
Deploy LLMs and agents where they add real business value, and skip them where they don’t. We’re not interested in AI for the sake of AI
Wire agents and systems together via APIs, webhooks, MCP servers, and lightweight code (Python, SQL, TypeScript). Use platforms like Clay, n8n, Workato, or Hightouch AI when they fit. Build custom when they don’t
Build signal pipelines that capture buying intent (hiring patterns, funding events, security disclosures, product telemetry from our own platform) and trigger the right agent or action automatically
Stand up the governance layer for every agent you ship: permissions, audit trails, access controls, sensitive data handling, and rollback paths
Build evaluation harnesses that measure real business outcomes (pipeline generated, deals accelerated, rep hours saved), not just whether the agent ran
Codify recurring patterns as reusable skills so the next agent doesn’t start from scratch
Document the architecture and write the runbook so the next person on the team can learn from your work
Expand into adjacent functions (Finance, People, Security ops) as the pattern proves out

Qualifications

Required

5+ years in RevOps, Growth Ops, GTM Engineering, Sales Engineering, or Solutions Engineering, with production work that other people relied on
Strong technical chops: fluent SQL, comfortable in Python or TypeScript, lives in APIs and webhooks, reasons cleanly about data flow and auth
Modern data stack experience in production: warehouse (Snowflake, BigQuery), transformation (dbt), Reverse ETL (Hightouch, Census). You’ve shipped this, not just read about it
Deep Salesforce or HubSpot. Custom objects, schema design, sync logic, the limits and workarounds. You have battle scars
Working knowledge of the modern GTM stack: Outreach or Salesloft, Gong, ZoomInfo, Clay, Apollo, LinkedIn Sales Navigator, product analytics
Production experience deploying LLMs and AI agents in GTM workflows. You don’t need to have built agent frameworks from scratch. You do need to have shipped something real and have informed views about what worked
Discovery instincts. You sit with the people doing the work before building. You ask the right questions and find the actual problem
Process thinking. You map full workflows including the messy human handoffs and have opinions about what should stay human
Judgment about revenue work. You can tell the difference between something that drives pipeline and something that just looks good in a dashboard
Strong sense for security, governance, and risk. This matters double at a product security company touching customer and prospect data
Self-directed. You can run a stakeholder conversation, define the process, and ship a v1 without a PM translating for you

Nice to have

Reverse ETL, CDP, or growth platform experience (Hightouch, Census, Segment, Rudderstack)
Hands-on experience with modern agent frameworks, MCP servers, evals, or current-generation agent SDKs
Prior work supporting a PLG motion or a sales-led-to-PLG transition
Public writing about your work (blog, Substack, talks). We value people who can explain their thinking
Familiarity with security buyer personas (CISOs, product security leaders, PSIRT teams)

Why This Role Matters

GTM teams across the industry are racing to bolt AI onto individual reps. We think the real unlock is engineering the revenue motion itself, with agents at the core and modern data infrastructure underneath. The people who can do that work, spanning technical depth, modern data fluency, and revenue process judgment, will be valuable for a long time.

You’d be the first inside Finite State.

Compensation

Our salary ranges are based on experience and geographic location:

$192,000 - $230,000

About Finite State

At Finite State, we're on a mission to secure the connected world. Our platform empowers product security teams to detect vulnerabilities, manage software supply chain risks, and ensure compliance across complex device ecosystems. From IoT to critical infrastructure, we provide unparalleled visibility into firmware and software components, helping organizations protect their products and customers.

We move with urgency and intent — we’re transparent, own outcomes, put customers first, speak up, and learn fast — turning evidence into action. CLARITY is how we move fast without breaking trust.

C - Customer first - Learn from customers. Ship with urgency.
L - Leverage - Outsource the routine. Own the result.
A - Agency - We take responsibility—end to end.
R - Results - Ship value. Improve fast.
I - Integrity - Speak up. Experiment boldly. Be kind.
T - Transparency - Clear context. Faster decisions.
Y - "Why" - Our mission—securing the connected products humanity depends on—is the reason Finite State exists. CLARITY is how we make that mission real, every day, at speed

Bold Innovation – We push boundaries, explore new ideas, and take initiative to solve complex problems.

The Finite State platform brings visibility and control to the supply chains that create connected devices and embedded systems—all in a simple to use platform and at the scale manufacturers need to keep device production on time and on budget. After unpacking and analyzing every file, configuration, and setting in a firmware build, the platform generates a complete bill of materials for software components, identifies known and 0-day vulnerabilities, shows a contextual risk score, and provides actionable insights that product teams can use to secure their software

We are proud to be an Equal Employer Opportunity employer. We do not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. Finite State is committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities.

Agent Systems Engineer, GTM & Internal Operations at finitestate | AI Job Board