Architect/Senior Full Stack Software Engineer

About the role

Trimble is a global technology company that connects the physical and digital worlds, transforming the ways work gets done. With relentless innovation in precise positioning, modeling and data analytics, Trimble enables essential industries including construction, geospatial and transportation. Whether it is helping customers build and maintain infrastructure, design and construct buildings, optimize global supply chains or map the world, Trimble is at the forefront, driving productivity and progress. The Trimble AECO segment provides digital construction solutions that increase precision and productivity for Architecture, Engineering, Construction, and Operations. What Makes This Role Great: In this role, you aren't just a coder; you are a technical founder building the systems that allow entire teams to move 40 percent faster. You will have the unique opportunity to pioneer Agentic AI within the AECO industry, moving from discovery to working MVPs in days and seeing your architectural decisions directly impact the efficiency of global infrastructure projects. Key Exciting Responsibilities: Agentic Orchestration & AI-First Engineering Agentic Prompt Engineering: Develop and optimize prompts using few-shot and zero-shot techniques to define autonomous, goal-oriented agent behaviors. Focus on enabling personalized insights, automated decision-making, and complex workflow orchestration. Translate high-level product requirements into precise technical specifications that AI agents can execute with 90%+ accuracy. Shift from Execution to Supervision: Lead the development of full-stack features by orchestrating AI agents (Cursor, Copilot, Gemini CLI) to generate code, documentation, and tests. Rapid Prototyping: Partner with Product Definers (PMs) and Designers to move from discovery to a working MVP in hours or days, not weeks. Systems Architecture & Technical Strategy Architectural Oversight: Establish the high-level system design and modular architecture that ensures our AI-generated components are scalable, secure, and maintainable. Feasibility & Risk Scanning: Conduct early-stage technical feasibility scans during the Discovery phase to identify "Materiality" and "Invest" gates. Systems Thinking: Design for extensibility. Ensure that the pod's output integrates seamlessly with the broader Trimble ecosystem and Agentic AI platforms. Entrepreneurial Leadership & Pod Collaboration Own the Outcome: Operate with high autonomy in a "Pod-style" environment. You are responsible for the technical viability and the ultimate success of the product features your pod ships. Navigate Ambiguity: Thrive in an "async-first" environment, turning vague customer pain points into concrete technical roadmaps. Mentor through Excellence: Raise the engineering bar by teaching other builders how to leverage AI tools effectively while maintaining rigorous standards for code quality and system observability. Automated Quality & Security AI-Assisted Testing: Supervise the generation of comprehensive unit, integration, and E2E test suites using AI, ensuring that velocity never comes at the expense of reliability. Security & Ethics: Implement "Security-by-Design" patterns to ensure that all AI-generated code meets Trimble's standards for data protection and responsible and ethical AI use. Essential Skills and Experience: 5+ years of professional software engineering experience , with a track record of owning complex production systems from end-to-end. AI-Native Proficiency: You must be an expert user of AI-assisted development tools (e.g., Cursor, GitHub Copilot, Claude Code, Gemini CLI). You understand how to debug AI "hallucinations" and maintain high engineering standards. Architectural Depth: Strong experience in designing distributed systems, microservices, and event-driven architectures (AWS/Azure). Full-Stack Fluency: Deep knowledge of Python (FastAPI/Flask) and modern frontend frameworks (React/TypeScript). Database & Data Modeling: Solid skills with PostgreSQL (schema design, indexing) and an understanding of how to architect data for AI consumption. Entrepreneurial Track Record: Experience in a startup or a "v1 to v2" product environment where you had to make trade-offs between speed and perfection. Strong Communication: Ability to articulate complex technical "intent" clearly to both AI agents and human stakeholders (executives and customers).