AI Agent Developer

Netskope (NASDAQ: NTSK) is a leader in modern security and networking for the cloud and AI era. We secure and accelerate cloud data and AI in real time everywhere. Thousands of customers including more than 30 of the Fortune 100 trust the Netskope One platform its Zero Trust Engine and the powerful NewEdge network to gain full visibility and control without performance trade-offs.

At Netskope our technology is driven by our greatest strength: our people. We believe that belonging powers innovation and success is both personal and organizational. We embrace differences in gender ethnicity beliefs ability and identity creating an environment where every voice is heard and respected. We empower our employees to bring their authentic selves to work grow their careers through continuous education and mentorship and lead with transparency and curiosity. Join a team where you belong where you are encouraged to be an entrepreneur and where together we continue to redefine the landscape of security.

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Moving AI agents from a playground demo to production requires serious software engineering discipline. We are looking for an AI Agent Engineer who knows how to build scalable secure and fully auditable agentic systems.

In this role you wont just tweak prompts until they feel right. You will build spec-driven orchestrator and sub-agent architectures manage sensitive data classifications integrate tool gateways and establish comprehensive test cases. Youll work closely with Product Security and Cloud Architecture to ensure every agent operates strictly within its designated guardrails and risk tiers.

Skills and Competencies:

• Write full agent specifications purpose capabilities input/output contracts guardrails and tool boundaries to the same level of rigor a safety-critical system would get not a quick README.
• Design and build orchestrator agents that hand work off to specialized sub-agents and hold the line on a simple rule: the orchestrator coordinates it doesnt do the work itself.
• Write and test system prompts and design tool schemas that stay accurate even when an agent has to choose between fifteen or twenty different tools not just three.
• Work with the Data Steward to classify how sensitive each agents data is and with the Product Owner/Architect to set its risk tier before anything goes up for registration.
• For each capability an agent has decide whether it should be deterministic logic or model judgment and build test cases that prove it actually meets that bar.
• Build every agent against the platforms tool gateway so nothing an agent does falls outside what its registered and approved to touch.
• Design for scale from day one sessions that stay isolated from each other failures that are predictable and no assumptions that only hold up in a single test run.
• Prepare the evidence a reviewer needs before approving an agent for production: test results guardrail coverage and behavioral results laid out clearly enough that someone outside your head can follow the reasoning.

• At least 4 years building production software with 12 of those years specifically spent building LLM-powered agents not chatbots not RAG pipelines agents that make tool-use decisions on their own.
• Real hands-on time with at least one agent orchestration framework LangGraph Bedrock AgentCore CrewAI AutoGen or similar enough to explain why youd pick one over another for a given problem.
• Working knowledge of the Model Context Protocol: building or integrating MCP servers and clients and understanding where tool-selection tends to break down.
• A real prompt engineering practice versioning changes testing them against a set of cases before shipping not just iterating in a playground until it feels right.
• Comfort writing precise specs: boundaries failure modes test criteria. This team documents everything and peer-reviews it so this isnt optional.
• Enough AWS familiarity (Lambda IAM roles Bedrock) to understand how your agents actually run even though infrastructure itself belongs to the Cloud Engineers.

• Experience designing systems where one agent does something and a different agent checks it separation of duties built into the architecture not just documented afterward.
• Any exposure to red-teaming or adversarial testing of AI systems even if it wasnt your main role.
• Time spent in a regulated environment (SOX SOC2 GDPR ISO27001) where it works was never the whole bar.
• Some familiarity with how agent memory works short-term session memory versus something more durable and what each choice costs you in auditability.

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The application window for this position is expected to close within 50 days. You may apply by filling out the below information or visiting ourNetskope Careers site.