Founding AI Platform Engineer

This test must be taken to be considered for this position. Aegis is building an AI security and governance platform focused on discovering, classifying, risk-scoring, and enforcing policies for AI agents, AI scripts, and automation workflows across enterprise environments. We are looking for a hands-on technical co-founder who can design, build, and ship the first MVP end to end.

This role combines full-stack engineering, AI/ML systems, cloud infrastructure, data pipelines, and security-focused product thinking. What You Will Build You will own the end-to-end Aegis Discovery MVP, including: AI agent discovery across cloud, repositories, SaaS logs, and runtime telemetry Data normalization pipeline using OpenTelemetry-style schemas Agent identity correlation across runtime, cloud, repo, and SaaS signals Agent fingerprinting to identify frameworks such as LangChain, CrewAI, LlamaIndex, AutoGen, and direct LLM SDK usage Risk scoring based on data sensitivity, autonomy, access scope, and behavior drift Policy recommendation logic using capability matching and policy templates Minimal discovery console to show agents, risk findings, and recommended policies Integration with existing Aegis runtime and SDK for policy enforcement The MVP goal is to produce a real agent record, real risk findings, and a real policy recommendation from an end-to-end demo path, not mocked outputs. Required Experience Ideal candidate has 4–5 years of strong hands-on engineering experience , with practical exposure to: Full-stack development: backend APIs, frontend UI, databases, and deployment Python and/or TypeScript AI/LLM application development using frameworks such as LangChain, LlamaIndex, CrewAI, AutoGen, OpenAI, Anthropic, or similar Cloud platforms, especially AWS Kubernetes, Docker, and basic DevOps PostgreSQL or graph-style data modeling Event pipelines, logs, telemetry, or observability systems Security concepts such as IAM, service accounts, audit logs, data sensitivity, and policy enforcement Building fast MVPs with clean architecture and practical trade-offs Strong Plus Experience with OpenTelemetry, eBPF, Pixie, CloudQuery, Vector, Semgrep, Apache Flink, OPA/Rego, or similar tools Experience building security, governance, compliance, or developer infrastructure products Familiarity with AI agent risks, shadow AI, data leakage, PHI/PII, and enterprise AI governance Key Traits We need someone who is: Highly hands-on and comfortable writing production-quality code Able to design architecture and also implement it personally Fast, practical, and MVP-focused Strong at debugging complex systems Comfortable with ambiguity Product-minded, not just engineering-minded Able to make technical trade-offs without overbuilding Interested in becoming a true technical co-founder, not just an employee This test must be taken to be considered for this position.