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Akshay Bankapure

@akshaybankapure

AI integration engineer building production LLM and ML systems with RAG, MLOps, and measurable enterprise impact.

India
Message

What I'm looking for

I want to bring my end-to-end LLM/ML integration into an enterprise consulting context—varied problems, larger scale, and AI work with measurable client impact—while owning architecture and ensuring responsible delivery.

I’m an AI/ML engineer with 7 years of experience building and deploying production-grade ML and AI systems across PropTech, healthcare, and enterprise domains. I work end-to-end across the AI lifecycle—data engineering, model development, LLM integration, RAG pipelines, and cloud deployment on AWS and Azure.

Currently, I’m leading AI product development at Sirrus.ai, where I own architecture decisions and mentor engineers while translating complex business requirements into working AI systems. Highlights include shipping a computer vision pipeline that converts 2D floor plans into navigable 3D models, building an MCP-based AI agent system embedded in the product UI, and delivering RAG pipelines with under 1% hallucination rate through retrieval scoring and prompt engineering.

I’m equally comfortable in stakeholder conversations and sprint planning, especially when responsible AI matters—output monitoring, confidence scoring, bias evaluation, explainability reporting, and human-in-the-loop workflows. Previously, at Autonomize AI, I built healthcare document intelligence integrations using Azure OpenAI and Hugging Face (with LoRA fine-tuning), improving accuracy and latency while strengthening the LLM-to-backend integration and hybrid retrieval with Azure Cognitive Search.

Experience

Work history, roles, and key accomplishments

SI
Current

Lead ML Engineer

Sirrus.ai

Jun 2024 - Present (2 years 1 month)

Own AI orchestration and data/storage architecture, running Agile sprints and coordinating ML, backend, and frontend delivery. Build and ship production GenAI/CV systems including an MCP-based AI agent and RAG pipelines using LangChain and ChromaDB, with responsible AI monitoring and multi-tenant data isolation.

AA

Senior Software Engineer

Autonomize AI

Sep 2023 - Dec 2023 (3 months)

Built the AI integration layer for a healthcare document intelligence platform using Azure OpenAI and Hugging Face models fine-tuned with LoRA for classification and NER. Designed Kafka-based ETL pipelines and implemented responsible AI practices including confidence scoring and human review workflows, plus hybrid retrieval with Azure Cognitive Search.

RP

Software Developer

Rig Control Products

Sep 2021 - Mar 2023 (1 year 6 months)

Developed real-time Python/Node.js/TypeScript systems for oil and gas sensor data processing and visualization, including low-latency pipelines and interactive monitoring UIs. Implemented ETL workflows, Azure DevOps CI/CD pipelines, and Azure cloud deployments, and improved reliability by validating communication protocols between software and field hardware.

RI

Software Developer

Racksons IT

Feb 2017 - Nov 2019 (2 years 9 months)

Delivered full-stack web development across Python and JavaScript frameworks, building client projects for e-commerce and enterprise applications with REST APIs and authenticated integrations. Owned backend and database responsibilities including JWT-secured APIs, microservices, Docker-based deployments, and cross-database schema/query optimization.

Education

Degrees, certifications, and relevant coursework

University of Dundee logoUD

University of Dundee

Master of Science (MSc) Computing, Computing

2020 - 2022

MSc Computing focusing on a low-cost LoRaWAN IoT data collection system for agricultural monitoring. Completed projects including deep learning for skin cancer multi-class diagnosis and an ETL pipeline for the SUN dataset.

NW

NIT Warangal

Postgraduate Diploma, Artificial Intelligence and Machine Learning

2019 - 2020

PG Diploma in Artificial Intelligence and Machine Learning with a capstone on an ML model for auto insurance risk prediction. Covered end-to-end pipeline work from data preparation and feature engineering through model selection and evaluation.

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