SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Salary: USD 90,000 - 160,000 / annual
Hatz AI is building infrastructure that enables businesses to adopt AI with confidence. As a Forward Deployed Engineer, you will partner with MSPs (Managed Service Providers) and their end-customers to transform AI capabilities into production systems. This role bridges customer delivery and core platform development, requiring equal parts engineering expertise, deployment execution, and product influence.
You will own the complete lifecycle of AI agent and workflow deployments in production environments, from initial discovery and technical scoping through system design, build, and production rollout. Working directly with MSP engineering teams and domain experts, you'll drive production adoption, measure workflow impact, and provide evaluation-driven feedback that shapes product and model roadmaps. You'll collaborate closely with Product, Partnerships, GRC, Security, and GTM teams.
Key responsibilities include:
- Leading technical delivery across multiple concurrent deployments, from prototype to stable production
- Building full-stack systems that deliver measurable customer value and inform product learning
- Representing Hatz in senior client settings (C-suite, CEOs, CMOs) with executive presence
- Embedding with MSP and customer teams to understand needs and guide adoption
- Scoping work, sequencing delivery, and removing blockers early
- Making sound trade-offs between scope, speed, and quality while protecting delivery timelines
- Codifying working patterns into reusable tools, playbooks, and building blocks
- Sharing field feedback to help Product understand platform strengths and improvement areas
- Maintaining team momentum through clarity and follow-through
The role is based in New York City (Flatiron District) with a hybrid schedule when not traveling. Expect approximately 50% travel to customer sites.
Requirements:
- 2–5+ years of engineering or technical deployment experience, including customer-facing work
- Track record of scoping and delivering complex projects in fast-moving or ambiguous environments
- Hands-on experience building or deploying systems powered by LLMs or generative models, with understanding of how model behavior shapes product experience
- Self-directed in ambiguity; ability to shape unclear asks into detailed workflows, flag issues early, and deliver without hand-holding
- Clear communication with engineers, product teams, and MSP stakeholders
- Composure and sound judgment under high-stakes conditions
Nice-to-haves:
- Experience writing or maintaining customer-facing documentation
- Proficiency in Python or familiarity with AI tools and complex software
- Experience with coding tools like Claude Code, Codex, or OpenCode
- Ability to contribute directly to the codebase when needed for progress or clarity
- Prior exposure to security and compliance workflows (SOC reports, DPAs, security questionnaires)
- Familiarity with incident management and on-call rotation practices
