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Arnab Mukherjee

@arnabmukherjee

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AI engineer building ultra-low-latency voice AI and production-grade LLM systems.

India

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What I'm looking for

I seek roles building production-grade voice and LLM systems with low-latency constraints, scalable multi-tenant architectures, strong engineering teams, and opportunities to drive measurable product and compliance impact.

I am an AI engineer specializing in ultra-low-latency voice AI systems, multi-tenant architectures, and production-grade LLM applications. I design real-time conversational AI using OpenAI Realtime API and Gemini, integrate telephony platforms like Twilio and Exotel, and deliver compliant solutions across healthcare, pharma, finance, and enterprise sectors.

My work includes engineering a 0.5s latency voice assistant, architecting multi-tenant voice infrastructure for 50+ organizations, building meeting intelligence and regulatory compliance automation systems, and deploying production AI on GCP with CI/CD and autoscaling. I focus on performance optimization, scalable orchestration, and measurable impact such as 70% faster loan processing and 10x faster documentation cycles.

Experience

Work history, roles, and key accomplishments

Current

Gen AI Engineer

Current

Atrina Technologies Pvt Ltd

Feb 2025 - Present (1 year)

Engineered ultra-low-latency voice assistant achieving 0.5s response time and architected multi-tenant voice AI infrastructure serving 50+ organizations, improving latency and tenant isolation while integrating enterprise telephony.

LiveKit Gemini Realtime API WebRTC Twilio Qdrant fastAPI GCP

Trainee - Data Science & AI

Bhabha Atomic Research Centre

Jan 2024 - Dec 2024 (11 months)

Developed CV-based radiation exposure detection achieving 85%+ accuracy and built end-to-end ML and NLP pipelines including GPT-3 report generation and geospatial predictive analysis for environmental monitoring.

K Means OpenCV CNN GPT 3 Kriging PyTorch Data Engineering Geospatial analysis

Education

Degrees, certifications, and relevant coursework

NCRD's Sterling Institute of Management Studies

Master of Computer Applications, Computer Applications

2022 - 2024

Grade: 8.89/10

Completed a Master of Computer Applications with a CGPA of 8.89/10, focusing on advanced software development, AI, and cloud-based production systems.

Ramniranjan Jhunjhunwala College

Bachelor of Computer Science, Computer Science

2018 - 2021

Grade: 8.58/10

Earned a Bachelor of Computer Science with a CGPA of 8.58/10, covering core CS topics including programming, data structures, and machine learning fundamentals.