AI Engineer

About this role

About Us At Pinpoint Global, we build training and compliance platforms that organizations rely on to keep their teams skilled, certified, and audit-ready. We're part of the Valsoft Edelweiss Software Group — a large-scale portfolio of vertical market B2B SaaS companies — and we operate with a startup mindset: high ownership, high velocity, and real ROI. Our core stack is ASP.NET MVC + MS SQL — battle-tested and ready to evolve. We're looking for true builders: engineers who orchestrate systems, ship production-grade AI, and modernize massive legacy codebases at speed. The Role You'll embed directly in our engineering team, working hands-on inside our .NET codebase and broader product suite. Your mission is to act as an organizational force multiplier — turning legacy inefficiencies into intelligent systems, increasing Net Revenue Retention (NRR), and driving measurable business impact through production-grade AI. This is a full-stack role with direct product impact. If you enjoy owning problems end-to-end, have a relentless bias toward action, and thrive on shipping real systems at high velocity — this role is for you. What You'll Do Build & Ship AI Systems Integrate AI capabilities (LLM APIs, intelligent automation, personalization) into our ASP.NET MVC products Design, develop, and deploy production-grade, secure AI systems using scalable polyglot microservices Integrate enterprise LLMs (Anthropic Claude, OpenAI, Google Gemini) into SaaS platforms via fault-tolerant API routing gateways Develop autonomous multi-agent workflows using parallel orchestration tools (Claude Code CLI, OpenAI Codex) Build new product surfaces — smart content recommendations, automated compliance tracking, AI-assisted reporting Rapidly prototype → validate via adversarial testing → deploy → iterate Architect AI Infrastructure Implement complex RAG pipelines and optimize trade-offs between massive-context hydration and multi-stage semantic retrieval Build vector databases (Pinecone, Weaviate, FAISS) and manage persistent document embedding queues Build polyglot microservices handling long-running tasks and streaming via 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 Modernize & Collaborate Identify high-impact modernization opportunities across our training and compliance platform Help 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 Work directly with non-technical stakeholders to translate ambiguous business problems into secure, scalable AI solutions Collaborate with product and design to ship features end-to-end Required Technical Skills Core Engineering 3–5+ years of enterprise software development experience with strong full-stack web fundamentals Hands-on experience with .NET / ASP.NET MVC (our core stack) and C# Fluency across popular languages and frameworks: Python, JavaScript, TypeScript, .NET, NextJS Solid understanding of relational databases — MS SQL experience a plus Backend experience designing polyglot APIs, decoupled async microservices, and persistent connection protocols (WebSockets/SSE) Familiarity with containerization (Docker, Kubernetes) and multi-region cloud infrastructure (AWS, Azure, or GCP) AI & ML Systems Practical experience integrating AI/ML APIs or building AI-powered features in production Enterprise LLM integration and dynamic API routing (OpenAI, Anthropic, Gemini) Multi-agent orchestration and advanced CLI tooling (Claude Code, OpenAI Codex) Mastery of AI IDE tooling: Cursor for repo-wide reasoning, GitHub Copilot RAG pipeline design: dynamic chunking, vector databases, embedding management Custom evaluations (LangSmith), structured outputs, and managed fine-tuning in secure cloud environments MLOps & Process Automation Zero-touch CI/CD pipelines and advanced Git workflows (including worktree isolation for autonomous sub-agents) Unit test and benchmark automation integrated 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 Points Experience with prompt engineering, RAG pipelines, or agentic workflows Familiarity with refactoring or re-architecting legacy .NET applications Background in regulated industries: HR tech, e-learning, compliance, LMS platforms Knowledge of SOC 2 audit requirements and compliance automation tooling Who You Are Highly hands-on — you ship, not just design; you operate at velocity by orchestrating autonomous tools Entrepreneurial startup mindset — you spot legacy inefficiencies and act with a bias toward rapid action Comfortable with ambiguity — you scope, own, and deliver independently Business-oriented — you care about ROI, operational leverage, and financial metrics like NRR and CAC Strong product instincts — you think about the user, not just the implementation Fast learner — you track real-time shifts in AI ecosystems, APIs, and infrastructure Pragmatic — you use the right secure enterprise tool for the bottleneck, not just the flashiest one Tech Stack ASP.NET MVC · C# · MS SQL · Python · TypeScript · LLM APIs (Anthropic, OpenAI, Gemini) · RAG / Vector DBs · Docker · Kubernetes · Azure / AWS / GCP · REST APIs · WebSockets · HTML/CSS/JS Why Join 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 a