Agentic Ai Engineer
Weekday AI View all jobs
- Chennai, Tamil Nadu
- Permanent
- Full-time
- Design and build AI-driven systems for reinforcement generation across structural elements such as walls, slabs, beams, and columns
- Develop geometry-aware pipelines that process BIM/IFC data and convert it into structured reinforcement outputs
- Implement rule-based logic for reinforcement placement, including spacing, cover, bends, laps, and constructability constraints
- Combine LLMs with deterministic systems to enable structured reasoning, validation, and workflow orchestration
- Build validation frameworks to ensure accuracy, compliance, and collision-free reinforcement layouts
- Generate structured outputs for downstream use, including visualization, editing, and bill of materials workflows
- Develop tools and workflows for visual inspection, review, and correction of generated outputs
- Handle complex edge cases and improve system reliability through testing, evaluation datasets, and debugging tools
- Collaborate with product, engineering, and domain experts to refine system capabilities and performance
- Contribute to backend architecture, APIs, deployment, and system optimization
- Strong experience in Python and backend system development
- Hands-on experience building AI or agent-based systems with structured outputs and workflow orchestration
- Solid understanding of computational geometry, coordinate systems, and transformation logic
- Experience working with structured data in CAD, BIM, or similar engineering domains
- Ability to translate complex engineering rules into scalable, testable systems
- Strong problem-solving and debugging skills with a systems-thinking approach
- Familiarity with IFC/BIM tools, geometry processing, or 3D modeling workflows is highly valuable
- Understanding of reinforcement detailing concepts or structural engineering workflows is a strong advantage
- Experience with visualization tools, evaluation pipelines, or production AI systems is a plus
- Proactive, detail-oriented, and comfortable working on complex, real-world engineering problems at scale