5-7 years of engineering experience with proficiency in Python and at least one of TypeScript/JavaScript, Java, or Go.
Strong curiosity about agentic AI and LLM systems, including prompt design and orchestration.
Ability to manage and analyze large-scale, messy data and understand cloud infrastructure.
Excellent communication skills to engage with both technical executives and frontline users.
Proactive and agile mindset, capable of iterating quickly based on user feedback.
Willingness to travel up to 25% for customer engagements.
Responsibilities
Embed with enterprise customers to rapidly deploy agent workflows on NinjaTech.
Integrate the platform with customer systems, creating tailored automations and tools.
Act as the technical representative for NinjaTech, facilitating discussions with various stakeholders.
Drive user adoption and identify opportunities for expanding the deployment across the organization.
Manage technical aspects of security reviews and compliance requirements.
Provide feedback to the product team based on field experiences to enhance future deployments.
Benefits
Full medical, dental, and vision coverage.
Meaningful equity options.
Delivery and expansion-linked bonuses.
Opportunity for onsite collaboration with the core team in the Bay Area.
Full Job Description
Why this role exists
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.
What you'll own
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.
What we require
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.
What we value (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.
Compensation & logistics
Base range $80K to $120K depending on level and experience, plus meaningful equity and a delivery/expansion-linked bonus.
Onsite in the Bay Area with the core team; ~25% travel to customer sites.
