Applied AI Engineer - AI Agent
About The Position
We’re a cybersecurity company building a next-generation AI-driven operations platform, designed to power complex, high-stakes workflows. The product integrates generative AI deeply into real-time operational environments—combining reasoning, retrieval, and automation into scalable, trustworthy systems. We’re looking for an Applied AI Engineer with strong backend and AI experience who can architect, build, and scale secure, performant systems. You’ll work closely with product, AI/ML, and design teams to deliver capabilities that drive investigation speed, streamline operations, and unlock new modes of human-AI collaboration.
Requirements
- Proven track record shipping data-intensive and AI-enhanced applications.
- BS: 5+ years in AI systems for high-availability, security-sensitive environments OR
- MS: 3+ years in the same OR
- PhD: 0+ year in the same
- Proficiency with at least one modern backend runtime/language (e.g., Python, Go) and associated frameworks.
- Strong background in designing APIs (REST/WebSocket/GraphQL) and integrating with real-time/event-driven systems.
- Deep understanding of databases and storage paradigms (e.g., Postgres, graph DBs, time-series stores).
- Experience with authentication/authorization, session management, and enterprise integrations.
- Familiarity with distributed systems, scalability, and observability best practices.
- Hands-on experience building or integrating AI systems in production.
- Familiarity with multi-agent, retrieval-augmented generation (RAG), prompt engineering, evaluation, and guardrails.
- Exposure to model fine-tuning workflows or orchestration frameworks for multi-tool AI agents.
- Strong problem-solving skills and attention to detail.
- Excellent written and verbal communication.
- Comfortable operating in fast-moving, ambiguous contexts.
- Experience working with distributed teams.
Responsibilities
- Architect and implement scalable AI agent and backend systems for high-volume, real-time operational workloads.
- Integrate LLMs and GenAI components into production workflows, including fine-tuning, prompt orchestration, retrieval pipelines, and evaluation loops.
- Design and implement robust data flows (e.g., event streams, message queues, job orchestration) to support next-gen SOC/NOC capabilities.
- Define clear contracts between AI services, backend APIs, and frontend clients.
- Contribute to trustworthy AI delivery: streaming responses with structured outputs, redaction/guardrails, and human-in-the-loop review.
- Partner with backend team to build data pipeline.
- Collaborate with design and frontend engineers to translate complex backend/AI systems into intuitive UIs.
- Lead technical reviews, and help shape coding standards and architectural patterns.
- Communicate clearly with both technical and non-technical stakeholders about trade-offs, performance, and reliability.
Benefits
- Opportunity to shape the future of AI-assisted cybersecurity and operations at scale.
- End-to-end ownership of high-impact product surfaces used daily by enterprise customers.
- Collaborative environment with experienced engineers, researchers, and designers.
- Continuous learning in AI/ML, distributed systems, and modern web technologies.
- Terrific benefits and competitive compensation.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
Ph.D. or professional degree
