Senior Agentic AI Engineer
 
Join a dynamic and fast-evolving team that is building next-generation AI-based tools and agent systems for the construction Industry. Our AI and Data Team is focused on designing intelligent AI agents, and copilots using modern AI/ML techniques.  

You will work closely with cross-functional teams, including business stakeholders, data engineers, and technical leads, to ensure alignment between business needs and data architecture and define data models for specific focus areas.  

What you'll work on 

▪ Build end-to-end Gen AI solutions - develop, refine, and implement advanced Gen AI models and ensure the success delivery of projects 
▪ Develop agents over our construction data estate, systems that answer non-trivial questions, take multi-step action against APIs and databases, and operate under governance constraints that matter.  
▪ Tool-use and orchestration design in LangGraph: defining the right granularity of tools, the right state machines, and the right human-in-the-loop checkpoints for a domain where wrong answers have real-world consequences. 
▪ Evaluation infrastructure for non-deterministic systems: building harnesses, golden datasets, and regression tests that let us ship agentic features with confidence. We treat eval as a first-class engineering problem, not an afterthought. 
▪ Retrieval and knowledge architecture spanning Snowflake Cortex, vector search, and structured graphs over our project data. You'll make real decisions about when retrieval is the answer and when it isn't. 
▪ Integration with our domain systems: partnering with engineers and analysts working on safety, operations, scheduling, and risk to turn agentic capabilities into tools superintendents and PMs use. 
▪ Technical direction-setting across the Agentic AI track: design reviews, architectural guidance, raising the bar on what "production-ready" means for agents, and mentoring engineers earlier in their agentic AI journey. 
▪ Collaborate with stakeholders, presenting findings to a non-technical audience and providing strategic recommendations. 
▪ Ensure the scalability, reliability, and security of AI solutions by implementing best practices for AI model development, deployment, and maintenance. 

Required Experience 

▪ 6+ years of production software engineering, with at least 2 years building LLM-powered systems in a production setting. 
▪ Demonstrated experience designing and shipping agentic systems using LangChain and LangGraph or comparable frameworks. 
▪ Strong Python engineering fundamentals: testing, packaging, performance, and the parts of the stack that aren't glamorous. 
▪ Practical experience with retrieval architectures (vector stores, hybrid search, reranking) and with at least one major cloud data platform. 
▪ Track record of evaluation work, you can describe specific eval systems you've built and what they caught that ad-hoc testing missed. 
▪ Excellent written and verbal communication, with experience presenting technical work to non-technical stakeholders.

Bonus

▪ Snowflake and Snowflake Cortex (Cortex Search, AI_COMPLETE, Cortex Analyst). 
▪ Experience with knowledge graphs or graph-augmented retrieval. 
▪ Familiarity with construction, AEC, or other physical-industry domains. 
▪ Experience working under AI governance frameworks like model risk, responsible AI, intake processes. 
▪ Open-source contributions to the LangChain/LangGraph ecosystem or related agentic tooling.