AI Platform Engineer Innovation Lab

Sector: Leading Financial Markets Infrastructure Organisation Location: Mumbai Experience: 6–8 years Grade: Manager / Senior Manager

Role Overview

This is a specialist AIplatform engineering role—distinct from generic Data Science or application development. The position demands deep expertise in MLOps/LLMOps, distributed inference, and GPUbased AI infrastructure, within regulated financial environments.

Key Responsibilities

- Architect and scale production AI systems for missioncritical financial applications.
- Lead MLOps/LLMOps pipelines and distributed modelinference frameworks.
- Engineer GPU infrastructure across sovereign/private cloud and onpremise environments.
- Implement enterprise AI gateways, semantic routing, failover mechanisms, observability, and guardrails.
- Drive GPU performance tuning, production troubleshooting, and CI/CD automation.
- Collaborate with crossfunctional teams to deliver secure, scalable AI innovation.

NonNegotiable Requirements

- Education:



BE/BTech/MCA in Computer Science, IT, Data Science, or related discipline.
- Experience: 6–8 years in software engineering or DevOps, including:
- 3+ years of handson production MLOps/LLMOps and distributed inference.
- 3+ years architecting and scaling production AI systems.
- Proven expertise in AIplatform engineering, distributed systems, GPU infrastructure.

- Handson proficiency with
- Languages/Frameworks: Python, FastAPI, AsyncIO, gRPC
- Inference Platforms: vLLM, NVIDIA Triton, TensorRTLLM, Ray Serve, Hugging Face TGI, llama.cpp
- Containers/Orchestration: Kubernetes, Docker, Helm, NVIDIA GPU Operator, KEDA
- Robust background in enterprise AI gateways, semantic routing, failover, observability, and guardrails.
- Expertise in GPU performance tuning, production troubleshooting, GitOps/CICD.

Interested candidates may share their CVs at:

📌 Manager/Senior Manager - Lead AI Platform Engineer (Mumbai)
🏢 Hiresquad
📍 Mumbai