Principal or Senior AI/ML Architect

General Description

The Principal AI/ML Architect owns architectural direction for the Intelligence and Agentic Workflows pillars of the Stratus Intelligence Platform. This role sets the technical direction every AI/ML and agentic project builds against, and is accountable for the long-term coherence, scalability, and trustworthiness of the AI-enabled platform. This is a player-coach role. Most time is spent hands-on: designing solutions, prototyping, leveraging AI tools, writing reference implementations, and reviewing critical PRs.

The Three Load-bearing Priorities

• Architect the Intelligence layer (data, training, learning, reasoning) and the Agentic layer (workflow automation, agentic UX).
• Stand up agent-friendly platform surfaces (MCP, Agent, or what fits at the time).
• Architect agentic UX and enable just-in-time interfaces where the platform generates tailored views.

Key Responsibilities

• Own the architectural vision and technical roadmap for Intelligence (data, learning, reasoning) and Agentic interfaces, workflows.
• Design and evolve agent-based workflows, enabling reasoning-capable, adaptive, multi-step systems with strong trust patterns (grounding, evals, confidence scoring).
• Develop and drive evaluation frameworks measuring model quality, agent reliability, drift, and platform effectiveness. Make AI workloads observable to engineering and product.
• Architect for simplify the core, customize at the edge. AI/ML capabilities are opinionated at the center, with foundations for marketplace or platform-exchange patterns at the edge.
• Architect agentic UX and enable just-in-time interfaces. The platform generates tailored views; we do not over-invest in heavy custom UI work.
• Build evaluation frameworks: model quality, agent reliability, drift detection, eval harnesses, observability for AI workloads.
• Drive AI-augmented engineering practice. Personally set the bar.
• Engage directly with customer-facing teams and customers to ground AI architectural decisions in real workflows.
• Mentor engineers; raise the technical bar through code review, design review, and technical coaching.

Qualifications

• 10+ years software engineering experience, with 5+ years in Principal, Staff+, or Architect roles at a B2B SaaS or AI/ML platform company.
• Demonstrated track record of leading AI/ML and agentic architecture across multiple teams or product lines.
• Experience designing systems where AI agents are first-class consumers: MCP servers, agent-facing APIs, retrieval-grounded interfaces.
• Deep proficiency in Python and the modern AI/ML stack (LangChain, LangGraph, PyTorch, sklearn, vector stores, embedding pipelines).
• Proficiency in C# / .NET and Azure for integration with Stratus's existing platform.
• Hands-on experience with RAG, fine-tuning, prompt engineering, model training and eval harness design.
• Hands-on experience with agent frameworks (LangGraph, AutoGen, CrewAI, Semantic Kernel, or equivalent) in production.
• Experience driving reliability and operational excellence for AI workloads in collaboration with a platform team.
• Comfortable contributing to and reviewing code across the stack.
• Excellent written and verbal communication.
• Track record of mentoring senior engineers and elevating the technical bar.

Nice to Have

• Background in security architecture and threat modeling for AI systems (prompt injection, data exfiltration, agent abuse) and B2B SaaS.
• Experience modernizing legacy ASP.NET MVC applications.
• Experience with Autodesk products (AutoCAD, Revit, Fabrication, BIM 360 Docs, Forge) or other MEP/AEC/CAD software.
• Domain knowledge of MEP, BIM, or construction technology workflows.
• Prior experience in a Series B / growth-stage company navigating the transition from product-market fit to scale.