Nandish Shah
@nandishshah
I’m a Senior AI Engineer building production-grade Generative AI systems.
IndiaWhat I'm looking for
I’m a Senior AI Engineer with 4+ years of hands-on experience architecting and shipping production-grade Generative AI systems, LLM-powered pipelines, and cloud-native backend platforms. I build beyond prototypes into scalable, enterprise-ready products.
I’ve led the design and delivery of CheckMate, a production AI platform for NDA legal risk analysis using RAG and LangChain—from document ingestion and chunking to multi-step LLM reasoning and structured JSON risk outputs. I also integrated Arize Phoenix to instrument spans, trace prompt-response chains, and monitor retrieval quality for hallucination and latency regression detection.
I design agentic workflows and event-driven infrastructure for reliability and throughput. At Ramboll, I orchestrated multi-agent systems with CrewAI and Agno, built CaminoAI for LLM-driven BPMN process generation with streaming output, and engineered Azure-based, fault-tolerant pipelines using Functions, Queue Storage, Blob, and Service Bus.
Earlier, I built an Azure-based analytics platform at Tata Consultancy Services, cutting data processing time by 89% (45 mins to 5 mins) by optimizing ETL pipelines in Azure Data Factory. I’ve also delivered computer vision and NLU work—deploying real-time attention monitoring with OpenCV and deep learning, and training a production-ready NLU model through Samsung’s PRISM program.
Experience
Work history, roles, and key accomplishments
Architected and shipped CheckMate, a production-grade AI platform for NDA legal risk analysis using RAG and LLM reasoning with structured JSON risk outputs. Built multi-agent enterprise workflows, deployed containerized Azure event-driven pipelines, and implemented end-to-end LLM observability with Arize Phoenix to monitor retrieval quality and hallucinations.
Designed and maintained Python-based automation infrastructure for large-scale energy engineering workflows, reducing manual effort and accelerating delivery timelines. Built RESTful APIs and backend services integrating domain algorithms, and improved deployment consistency by introducing Docker-based containerization and CI/CD practices.
Engineered an Azure-based analytics platform delivering real-time dashboards for global manufacturing operations. Reduced data processing time by 89% (45 mins to 5 mins) by redesigning ETL pipelines, and deployed anomaly detection on live sensor streams to enable early-warning alerts.
Computer Vision Engineer
Ajna AI
May 2020 - May 2021 (1 year)
Built real-time student attention monitoring software using computer vision and deep learning, deployed across SRM University and partner colleges with live video stream processing. Developed security and behavioral analysis solutions with OpenCV and deep learning, and delivered retail vision analytics combining object detection and spatial analysis.
Conducted applied research in natural language understanding (NLU) as part of Samsung's PRISM university program. Designed, trained, and delivered a production-ready NLU model and application, improving intent classification accuracy against real-world conversational benchmarks.
Education
Degrees, certifications, and relevant coursework
SRM University
Bachelor of Technology, Information Technology
2017 - 2021
Grade: GPA: 3.58 / 4.0
Bachelor of Technology in Information Technology at SRM University (2017–2021), achieving a GPA of 3.58/4.0.
Tech stack
Software and tools used professionally
Availability
Location
IndiaAuthorized to work in
Job categories
Skills
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