▪ 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.
Explore our open opportunities at www.dpr.com/careers .
Benefits
Health insurancePerformance bonus
Additional Information
Job Description
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.
Mydpr · Atlanta, GA