Staff AI Engineer

We are seeking a Staff AI Engineer to help build next-generation cybersecurity AI products for enterprise security teams.

This is a hands-on individual contributor role for an engineer who combines strong AI engineering capability, practical software development skills, and a strong interest in cybersecurity.

Key Responsibilities:

• Design and Build Advanced Cybersecurity AI Products
• Build agentic AI workflows for various cybersecurity operations, engineering, and risk processes.
• Convert ambiguous product ideas and early prototypes into secure, maintainable, production-grade AI systems
• Take end-to-end Technical Ownership of Complex AI Product Components, from problem framing to production operation.
• Break down ambiguous problems into technical plans, milestones, risks, and deliverables
• Contribute to technical roadmaps and influence prioritization through evidence, customer feedback, and engineering principles
• Identify design gaps, tech-debts, scalability risks, and make sound engineering trade-offs.
• Research, Evaluate, and Operationalized Emerging AI Technologies
• Continuously Learn, Research and Evaluate Emerging AI technologies
• Translate research findings into practical implementation patterns, product features, internal recommendations, or technical standards
• Share findings through technical documentation, demos, internal talks or fast POCs
• Build Production-Grade AI Products
• Develop backend services, APIs, integrations, AI orchestration, data pipelines, and other software components.
• Support deployment, monitoring, debugging, and operational support of AI products
• Work with CI/CD pipelines, containers, infrastructure as code, logging, metrics, and automated testing
• Design systems that scale across customers, workloads, data sources, and platforms
• Influence Through Technical Excellence
• Provide technical guidance to other engineers through code reviews, design discussions, documentation, and example implementations
• Mentor less experienced engineers informally through strong engineering practice and clear reasoning
• Raise the quality of team decisions by bringing evidence, research, customer context, and practical trade-off analysis
• Communicate complex AI, security, and architecture concepts clearly to technical and non-technical stakeholders
• Collaborate with product, security, solution engineering, and customer-facing teams to ensure product capabilities address real customer workflows
• Demonstrate ownership, proactiveness, customer obsession, and ability to operate effectively in ambiguity

Qualifications:

• Experience: 5+ years of professional experience in AI engineering and software engineering.
• 3+ years of hands-on experience building AI/ML, LLM-based, automation, data-driven, or intelligent software systems.
• Experience building production software, not only prototypes or notebooks.
• Experience working in product engineering teams or delivering customer-facing technical solutions.

AI Engineering:

• Strong practical experience with LLM applications, AI workflow automation, AI assistants, copilots, or agentic AI systems.
• Familiarity with concepts such as: prompt engineering, system prompts and instruction design, retrieval-augmented generation, vector search, embeddings, tool calling, function orchestration, context management, agent memory, evaluation datasets, model benchmarking, feedback loops
• Experience with agentic AI frameworks or tools such as: LangChain, LlamaIndex, Semantic Kernel, AutoGen, CrewAI, vector databases, knowledge graphs, model evaluation frameworks
• Ability to evaluate AI outputs objectively and improve quality, safety, reliability, latency, and cost.
• Experience using commercial or open-source AI models and APIs.
• Demonstrated ability to use AI tools in everyday work for coding, debugging, research, documentation, testing, or productivity improvement.

Software Engineering:

• Strong programming ability in two or more languages such as: Python, TypeScript / Node.js, Go, Java, Rust
• Strong understanding of software architecture, API design, data modeling, distributed systems, asynchronous processing, observability, and maintainability
• Experience building backend services, APIs, data pipelines, integrations, or cloud-native applications.
• Familiarity with web applications, distributed systems, databases, CI/CD pipelines, logging, monitoring, and automated testing.
• Ability to write clean, maintainable, secure, and production-ready code.
• Experience participating in design reviews, code reviews, and production troubleshooting.

Cybersecurity and Secure AI Awareness:

• Working knowledge of cybersecurity principles, secure software development, and common vulnerabilities.
• Ability to assess security implications of AI-enabled workflows and software architecture decisions.
• Interest and ability to deepen cybersecurity domain expertise quickly.
• Awareness of AI-specific security risks, including prompt injection, data leakage, hallucination, adversarial inputs, unsafe tool execution, and excessive permissions.

Cloud and Infrastructure:

• Experience developing or deploying applications on cloud platforms such as AWS and/or Microsoft Azure.
• Familiarity with containers, serverless services, managed databases, event-driven systems, queues, object storage, and cloud identity concepts.
• Understanding of observability, deployment automation, environment configuration, and operational reliability.
• Awareness of cloud security principles, IAM, secrets management, and secure configuration.

Leadership Qualities:

• Strong ownership mindset and accountability for outcomes.
• Proactive approach to identifying problems and proposing solutions.
• Customer-obsessed mindset with focus on practical user value.
• Comfortable dealing with ambiguity and evolving requirements.
• Strong analytical and problem-solving skills.
• Clear written and verbal communication skills.
• Strong habit of continuous learning, experimentation, and knowledge sharing.
• Ability to work independently and collaborate effectively in a small, fast-moving team.