Sobre esta vaga de Head of GTM Engineering & Systems na Fireworks AI
About Us:
At Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.
The Role
Our GTM team is growing 10x. As the leader of GTM Engineering you will set the architecture, drive our AI roadmap, or deliver on the auto-magical future that empowers every customer facing role.
You'll own the full GTM tech stack: Salesforce, CPQ, enrichment, engagement tooling, and the connective tissue between systems serving a growing org of BDRs, AEs, SAs, and managers. You'll also be the person who brings agentic AI from concept to production for our GTM teams, not as an experiment, but as the new operating baseline.
This is a builder and leader role. We're not looking for someone to manage vendors or coordinate rollouts. We want someone who will make hard architectural decisions, ship fast, and raise the bar for what great looks leading a GTM Engineering team.
What You'll Own
1. GTM Tech Stack and AI Foundations
Own every tool the GTM organization runs on: Salesforce architecture, enrichment layer (Clay, Harmonic, Sumble), routing (LeanData), engagement (Gong, Lemlist, Granola), and the integrations between them. As we scale from roughly 50 to 300+ GTM team members, the architectural decisions you make now are the ones that compound.
2. Quoting and Lead-to-Revenue Architecture (0 to 1)
We don't have a real CPQ solution today. Deal approvals run through Slack, order forms are built in Google Docs, and the billing handoff is fragile. You'll build a durable quoting and lead-to-revenue architecture from scratch, whether that's native Salesforce CPQ, a purpose-built tool, or a custom solution. The goal: an AE can take a deal from pricing to signed order form without RevOps as a bottleneck.
3. Agentic Workflows for GTM Teams
BDRs, AEs, SAs, sales managers, and RevOps are all under-leveraging AI today. You'll build the workflows that change that: AI-assisted account research, rep-facing deal intelligence, automated pipeline hygiene, manager insights. These should be workflows the team can't imagine working without, not demos.
4. Build and Scale the GTM Engineering Team
You're inheriting two strong engineers. You'll grow from there: defining hiring profiles, setting technical standards, building career paths, and maintaining a culture where high-quality, fast-shipping work is the norm.
Minimum Qualifications
- 10+ years in GTM Engineering, Revenue Operations, or Sales Operations at B2B companies; Consumption business model experience strongly desired
- 5+ years of people management experience
- Has architected in Salesforce at real depth: data model, process automation, integrations, governance — and knows how to take advantage of today’s modern CLI/MCP setups
- Has driven real world sales rep productivity enhancements measured in $s not time saved.
- Has built or rebuilt a quoting or CPQ workflow at meaningful scale
- Has led a team and set technical direction, not just managed execution
- Track record of building automation that sales reps actually use
Preferred Qualifications
- Has shipped agentic or AI-native GTM workflows in production (not pilots)
- Experience scaling GTM systems through a high-growth phase (Series B to D)
- Familiarity with usage-based or consumption pricing models
- Has worked at an AI/ML infrastructure, developer tools, or API-first company
Total compensation for this role also includes meaningful equity in a fast-growing startup, along with a competitive salary and comprehensive benefits package. Base salary is determined by a range of factors including individual qualifications, experience, skills, interview performance, market data, and work location. The listed salary range is intended as a guideline and may be adjusted.
Why Fireworks AI?
- Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.
- Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.
- Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.
- Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.
Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
