Senior Frontend Engineer – GenAI

1.  ABOUT THE ROLE

We’re a cybersecurity company building a next-generation generative AI platform used across multiple product surfaces - from analyst workflows to internal operations tools. We’re looking for a Senior Frontend Engineer with a strong frontend focus to design, build, and scale intuitive, high-performance experiences for data-heavy, real-time use cases.

You’ll work across the stack (with emphasis on the web frontend) to turn advanced AI capabilities - reasoning, retrieval, and automation - into trustworthy, efficient user experiences. You’ll collaborate closely with design, product, and AI/ML teams to ship features that improve investigation speed, streamline operations, and elevate customer outcomes.

1. KEY RESPONSIBILITIES

2.1 Development

• Own end-to-end delivery of user-facing features across investigative, assistive, and summarization surfaces - from proof-of-concept to launch and iteration.
• Design interactive dashboards, timelines, and graph/entity views that handle high-volume, streaming data with intuitive drill-downs and filtering.
• Build resilient real-time UX (e.g., WebSocket/SSE) and a scalable state architecture for conversations, incidents, and tickets, with reliable cross-view synchronization.
• Define clear API/data contracts, contribute to backend endpoints as needed, and integrate enterprise systems (ticketing, knowledge bases, telemetry/observability, workflow tools).
• Implement trustworthy AI UX: streaming responses with citations, guardrails/redaction, and human-in-the-loop review; capture feedback to improve prompts and behaviors.
• Instrument and improve outcomes - latency, error rates, summary accuracy, and user satisfaction - to reduce time-to-response and time-to-resolution.

2.2 Collaboration

• Work closely with backend, AI, product and design teams to translate complex requirements into elegant UIs
• Mentor engineers, lead design reviews, and evolve coding standards and best practices
• Communicate tradeoffs and architecture decisions clearly to technical and non-technical stakeholders

 

1. REQUIRED QUALIFICATIONS

3.1 Experience

• 5+ years of professional frontend development experience (full-stack a plus)
• Track record of shipping complex, data-intensive web applications at scale
• Experience operating in high-availability, security-sensitive or support-critical environments
• Demonstrated ownership from architecture through delivery

3.2 Technical Skills

Core Skills (Must Have)

• Expert proficiency with modern JavaScript/TypeScript and a component-based web framework (e.g., React)
• Experience with server-rendered web apps and routing
• Strong grasp of state management patterns (e.g., state containers, signals, or equivalent)
• Proficiency with async data fetching and caching for server state (e.g., query/fetch layers)
• Advanced CSS skills (responsive layouts, design systems, accessibility)
• Experience with real-time transports (e.g., WebSocket, Server-Sent Events) and streaming UX
• Git-based workflows and CI/CD; feature flagging and progressive delivery
• Comfort with charting/graph visualization libraries and building interactive, drill-down dashboards
• Understanding of UX for dense, high-stakes, data-heavy applications
• Experience working within and evolving component libraries/design systems

Communication & Soft Skills (Very Important!)

• Excellent written and verbal communication
• Strong problem-solving skills and attention to detail
• Self-directed, collaborative, and comfortable with ambiguity in fast-moving contexts
• Experience working with distributed teams

Backend & Platform (Nice to Have for Full-Stack)

• Experience designing APIs (REST/Websocket) and integrating with event streams
• Comfort with at least one server runtime/language (e.g. Python, Golang) and data storage paradigm (e.g Postgres, Neo4j)
• Understanding of authentication/authorization patterns and session management

 

1. PREFERRED QUALIFICATIONS (BONUS POINTS)

AI/ML Product Experience

• Built user experiences for generative AI features (assistive workflows, agent-style tool use, or similar)
• Understanding of LLM streaming patterns, tool orchestration, and structured outp