Founding AI Platform Engineer

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 must be taken to be considered for this position.