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AI Engineer

Valsoft Corporation · Remote, Canada

Data Science / AI / Machine LearningRemoteExternal listingfull-timeabout 4 hours ago

About The 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 and iterates fast
  • Startup velocity inside an established, well-resourced corporate portfolio

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