Job Summary
As an Sr Engineer on the AI Enablement team, you will be a hands-on builder and a force multiplier for how the broader Keystone engineering org works with AI. You'll split your time between scaling engineering practice and shipping autonomous agents that do real work — not prototypes that stall after a demo.
This role requires strong software engineering fundamentals, comfort operating with ambiguity on a fast-moving small team, and the judgment to know when an AI-generated answer is good enough to ship versus a production risk.
Job Responsibilities
- Scale engineering with AI
- Drive spec-driven, agentic-IDE development workflows (Cursor, Claude Code) across the team, from spec to implementation to review, so AI usage translates into measurable velocity, not just novelty.
- Define and evolve quality gates for AI-generated code: what changes in review, CI, and merge criteria when a large share of PRs are AI-assisted.
- Build and maintain shared skills, prompts, and MCP tooling that other Keystone engineers reuse, reducing redundant AI infrastructure across teams.
- Build production AI agents on the enterprise stack
- Design and ship agent workflows (planner vs. fixed-workflow, state/retries, human-in-the-loop checkpoints) that automate real toil
- Build well-scoped MCP tools/integrations against enterprise systems with clear schemas, auth boundaries, idempotency, and explicit rules on what data never reaches the model.
- Own evals and guardrails for agents in production: offline golden sets, online sampling, canary/rollback paths, and hard checks on numeric/PII/outbound-send correctness — distinguishing tool failures from model failures.
- Design for operational readiness from day one: what breaks under a 10× usage spike before quarter close, what the kill switch looks like when an agent gets a fact wrong, and how incidents get triaged.
Job Requirements
- Bachelor's degree in Computer Science, Engineering, or a related field; or equivalent, relevant experience.
- 8+ years of professional software development experience, with proven ownership of at least one system or domain end-to-end.
- Production experience with LLMs - prompt engineering, agent development, and evaluation frameworks.
- Hands-on experience building agent harnesses: tool calling, state/session management, retries, guardrails, and stop conditions for long-running agent workflows.
- Deep, hands-on proficiency in Python/Go/Java
- Experience with agent/orchestration frameworks (LangChain, LangGraph, or equivalent) and MCP or similar tool-calling standards, integrated with enterprise systems
- Working knowledge of AI-native, spec-driven development workflows (agentic IDEs like Cursor/Claude Code) and defining quality gates for AI-generated code.
- Strong problem decomposition and stakeholder navigation - able to scope an ambiguous cross-functional ask into a shippable plan and own it end-to-end, forward-deployed-engineer style.
Education
IC - Typically requires a minimum of 8 years of related experience.Mgr & Exec - Typically requires a minimum of 6 years of related experience.
Compensation:
The target salary range for this position is 170,000 - 253,000 USD. The salary offered will be determined by the candidate's location, qualifications, experience, and education and may be outside of this range. The range is based on 'On Target Earnings’ (OTE) representing the total potential earnings, which is the sum of the base salary and potential commission earned when performance targets are achieved. Final compensation packages are competitive and in line with industry standards, reflecting a variety of factors, and include a comprehensive benefits package. This may cover Health Insurance, Life Insurance, Retirement or Pension Plans, Paid Time Off, various Leave options, employee stock purchase plan, and/or restricted stocks (RSU’s). These offerings are subject to regional variations and governed by local laws, regulations, and company policies. We will provide detailed information about the specific benefits for your region during the recruitment process.
At NetApp, we embrace a hybrid working environment designed to strengthen connection, collaboration, and culture for all employees. This means that most roles will have some level of in-office and/or in-person expectations, which will be shared during the recruitment process.
Equal Opportunity Employer:
NetApp is firmly committed to Equal Employment Opportunity (EEO) and to compliance with all federal, state and local laws that prohibit employment discrimination based on age, race, color, gender, sexual orientation, gender identity, national origin, religion, disability or genetic information, pregnancy, protected veteran status, and any other protected classification.
Why You'll Thrive at NetApp
At NetApp, you won't wait for the perfect moment—you'll make it. The early planning, the extra thought, the bold idea that turns good into great: That's how our people operate and how we continue to push the boundaries of data infrastructure.
NetApp is the trusted partner for organizations transforming data into opportunity. As the only enterprise-grade storage service natively embedded in Google Cloud, AWS, and Microsoft Azure, we empower customers to run everything from traditional workloads to enterprise AI with unmatched performance, resilience, and security.
Our culture
We celebrate mold breakers, bold thinkers, and problem solvers. We reward initiative, impact, and ownership. We provide flexibility so you can balance professional ambition with your personal life. Here, differences are not just welcomed—they drive everything we do.
If you're ready to innovate, rise to the challenge, and own every moment - make your next move your best one. Apply now.
Submitting an Application
To ensure a streamlined and fair hiring process for all candidates, our team only reviews applications submitted through our company website. This practice allows us to track, assess, and respond to applicants efficiently. Emailing our employees, recruiters, or Human Resources personnel directly will not influence your application.
AI Disclosure
For select roles, some stages of our hiring process may use artificial intelligence tools to help evaluate applications and candidate selection. These tools support—rather than replace—human decision-making.