Applied AI Engineer
About The Position
When we close a large enterprise deal, the contract is the start of the hard part, not the end. The customer has bought an outcome, an "unmetered intelligence workforce" doing real work inside their business, and someone has to make that outcome real, fast, inside their systems, their security constraints, and their messy data. That someone is the Applied AI Engineer. We attach an Applied AI Engineer to every large enterprise account. They embed with the customer, build the first high-value agentic workflows on our platform, and own technical success from kickoff through go-live and expansion. The Applied AI Engineer is how a signed contract becomes a renewed and expanded one.
Requirements
- Engineering background. You're a genuine builder. Proficient in Python and at least one of TypeScript/JavaScript, Java, or Go; comfortable across data plumbing, APIs, and a bit of front-end when a demo needs it.
- Genuine curiosity about agentic AI and LLM systems: prompt/tool design, evals, orchestration, guardrails, and the failure modes of agents in production. You don't need to have built them at scale, but you should be hungry to.
- Data fluency. You can wrangle messy, large-scale, real-world data and reason about storage, pipelines, and cloud infrastructure.
- Executive presence and operator empathy. You can hold a credible technical conversation with a CTO and sit with a frontline user to understand their actual workflow. You listen before you build.
- Bias to ship. You move with speed and precision, iterate with users, and are energized (not frustrated) by evolving objectives.
- Willingness to travel up to ~25% to customer sites, and to be onsite in the Bay Area with the core team.
Nice To Haves
- Experience integrating into regulated or security-sensitive enterprise environments (isolated VMs, on-prem/VPC, SOC 2, HIPAA, FedRAMP-adjacent).
- Prior forward-deployed / solutions-engineering / delivery experience at an enterprise-software or infra company.
- A track record of turning a first deployment into a much larger footprint.
Responsibilities
- Land the deployment. Embed with a newly-closed enterprise customer, rapidly learn their operations and data, and stand up the first production agent workflows on NinjaTech in weeks, not quarters.
- Build custom, tailored solutions. Wire our platform into the customer's real systems (their data sources, identity, ticketing, CRMs, internal APIs) and build the bespoke automations, prompts, tools, and guardrails that make agents useful for their jobs-to-be-done.
- Be the technical face of NinjaTech in the room. Run working sessions with everyone from the customer's frontline operators to their CISO and CTO. Translate their vision into an architecture, and translate our platform into their language.
- Drive adoption and expansion. A deployment that isn't used doesn't renew. Instrument usage, hunt for the next high-value workflow, and turn a beachhead into an org-wide rollout. Your success metric is customer outcomes that drive net revenue retention.
- Clear enterprise gauntlets. Own the technical side of security review, isolated-VM/data-residency requirements, SSO/SCIM, SOC 2 / DPA questionnaires,and procurement's technical due diligence.
- Close the loop to Product. You see what breaks in the field first. Feed sharp, prioritized signal back to core engineering; occasionally upstream a fix or a reusable component so the next deployment is faster.
Benefits
- Full benefits (medical / dental / vision, etc.)
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
