AI code licensing program assessing existing software repositories for licensing value. Compensating eligible code owners under agreed non - exclusive licensing terms.
About the role
- AI Engineer embedding LLMs, RAG, and multi-agent systems into compliance training SaaS. Modernizing ASP.NET products and deploying secure AI infrastructure at startup velocity.
Responsibilities
- Integrate AI capabilities such as LLM APIs, intelligent automation, and personalization into ASP.NET MVC products
- Design, develop, and deploy secure, production-grade AI systems using scalable polyglot microservices
- Integrate Anthropic Claude, OpenAI, and Google Gemini into SaaS platforms through fault-tolerant API routing gateways
- Develop autonomous multi-agent workflows using Claude Code CLI and OpenAI Codex
- Build product surfaces including smart content recommendations, automated compliance tracking, and AI-assisted reporting
- Rapidly prototype, validate through adversarial testing, deploy, and iterate
- Implement complex RAG pipelines and optimize massive-context hydration versus multi-stage semantic retrieval
- Build and manage vector databases such as Pinecone, Weaviate, and FAISS, including persistent document embedding queues
- Build polyglot microservices for long-running tasks and streaming through WebSockets and Server-Sent Events
- Ensure SOC 2 compliance, data residency controls, and deterministic execution through policy-as-code agentic governance
- Deploy and scale models within secure managed cloud boundaries
- Identify high-impact modernization opportunities across the training and compliance platform
- Migrate legacy features into scalable, AI-native architectures using agentic swarm coding and automated refactoring
- Architect zero-touch CI/CD pipelines with adversarial gating and AI-driven test automation
- Integrate synthetic red teaming into CI/CD to prevent prompt drift, reward hacking, and logic degradation
- Translate ambiguous business problems into secure, scalable AI solutions with non-technical stakeholders
- Collaborate with product and design to ship features end-to-end
Requirements
- 3–5+ years of enterprise software development experience with strong full-stack web fundamentals
- Hands-on experience with .NET / ASP.NET MVC and C#
- Fluency across Python, JavaScript, TypeScript, .NET, and NextJS
- Solid understanding of relational databases; MS SQL experience is a plus
- Backend experience designing polyglot APIs, decoupled async microservices, and WebSockets/SSE
- Familiarity with Docker, Kubernetes, and multi-region cloud infrastructure on AWS, Azure, or GCP
- Practical experience integrating AI/ML APIs or building AI-powered features in production
- Enterprise LLM integration and dynamic API routing using OpenAI, Anthropic, and Gemini
- Multi-agent orchestration and advanced CLI tooling, including Claude Code and OpenAI Codex
- Mastery of Cursor and GitHub Copilot
- RAG pipeline design, including dynamic chunking, vector databases, and embedding management
- Custom evaluations with LangSmith, structured outputs, and managed fine-tuning in secure cloud environments
- Zero-touch CI/CD pipelines and advanced Git workflows, including worktree isolation for autonomous sub-agents
- Unit test and benchmark automation with AI-driven testing frameworks
- Adversarial LLM testing and automated synthetic red-teaming
- Hallucination mitigation, enterprise guardrails, and deterministic policy-as-code execution
- Real-time token/credit consumption tracking and dynamic access limit monitoring
- Bonus: experience with prompt engineering, RAG pipelines, or agentic workflows
- Bonus: familiarity with refactoring or re-architecting legacy .NET applications
- Bonus: background in HR tech, e-learning, compliance, or LMS platforms
- Bonus: knowledge of SOC 2 audit requirements and compliance automation tooling
Benefits
- Shape the AI strategy of a growing compliance and training platform
- Own meaningful features from day one — not just tickets in a backlog
- Real modernization challenge: legacy codebase + greenfield AI opportunity in parallel
- Collaborative, low-ego team that ships and iterates fast
- Startup velocity inside an established, well-resourced corporate portfolio
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