AI Engineer

Valsoft Corp.

$120K — $145K *
US-AnywhereRemote in Canada
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 3-5+ years of full-stack enterprise software development experience
  • Proficient in .NET / ASP.NET MVC and C#
  • Fluency in languages such as Python, JavaScript, TypeScript, and NextJS
  • Strong knowledge of relational databases, especially MS SQL
  • Experience building polyglot APIs and asynchronous microservices
  • Familiarity with containerization tools like Docker and Kubernetes

Responsibilities

  • Integrate AI capabilities into ASP.NET MVC products
  • Design and develop secure, scalable AI systems using microservices
  • Implement dynamic API routing for enterprise LLM integration
  • Develop workflows using multi-agent orchestration tools
  • Identify opportunities to modernize legacy systems
  • Architect CI/CD pipelines to incorporate AI-driven test automation

Benefits

  • Opportunities for hands-on participation in high-impact projects
  • Direct engagement with a dynamic engineering team
  • Access to cutting-edge technologies in AI and cloud infrastructure
  • A chance to work in an entrepreneurial and fast-paced environment
  • Collaboration with product and design teams on innovative features
Full Job Description
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 1 validate via adversarial testing 1 deploy 1 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 3 3 MS SQL 3 Python 3 TypeScript 3 LLM APIs (Anthropic, OpenAI, Gemini) 3 RAG / Vector DBs 3 Docker 3 Kubernetes 3 Azure / AWS / GCP 3 REST APIs 3 WebSockets 3 HTML/CSS/JS

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