Engineering Manager - Artificial Intelligence Engineering

Meesho; Bengaluru; On-site; INR 3,500,000 - 5,200,000; Full time

Job summary

Meesho in Bengaluru is seeking an Engineering Manager for AI Engineering to lead scalable AI platforms and infrastructure, guiding a high-performing team and delivering production-grade systems powering AI use cases across Meesho.

You will shape technical direction, drive cross-region model inference, GPU optimization, and end-to-end delivery while collaborating with Product, Data Science, and Platform teams.

Qualifications

• Minimum 9+ years of software engineering experience, with 2+ years in people management.
• Strong hands-on expertise with modern AI inference stacks and production-grade serving at scale.
• Proven ability to lead multi-disciplinary teams across AI, platform, and product teams.

Responsibilities

• Lead, mentor, and grow AI engineers; set technical direction and ensure delivery end to end.
• Architect and scale the AI platform for cross-region model inference and distributed training.
• Drive optimization across GPU kernels, quantization, and memory/bandwidth for low latency serving.
• Scale data-science productivity with autonomous agent-driven workflows from feature engineering to rollout.
• Partner with Product, Data Science, and Platform teams to deliver production impact for millions of users.
• Own operating rhythm: hiring, performance reviews, sprint planning, and OKRs.

Skills

Leadership & people management

Python

GPU programming (CUDA)

Kubernetes / GKE

PyTorch / DeepSpeed / Megatron / Ray

LLM inference & AI infra

Distributed systems / MLOps

Observability / SLOs

Big data / streaming (Spark, Flink)

Open-source contributions (ML infra)

Education

Bachelor's or Master's in Computer Science

Tools

TensorRT-LLM

vLLM

SGLang

PyTorch FSDP

DeepSpeed

Megatron

Ray

Kubernetes (GKE)

Spark

Flink

Job description

Engineering Manager – AI Engineering

About Meesho

Meesho is India's fastest-growing internet commerce company, on a mission to democratize e-commerce for everyone. We serve millions of customers and over 1.75 million sellers through technology-driven innovation, building the scalable systems that power Meesho's most critical surfaces — Search, Recommendations, Personalized Ranking, Logistics, Fraud Detection, and Image Match. The AI Platform sits at the heart of this. It serves a peak of 1M+ real-time deep-learning model inferences per second on ordinary days, scaling 3x+ on sale days — with the reliability that scale demands. The team works at the frontier of applied AI and infrastructure — multi-region inference, novel embedding-search algorithms, and optimized open-weight LLM models — squeezing out every bit of computation and passing the cost savings straight back to customers.

About the Role

We are looking for an experienced Engineering Manager – AI Engineering to lead the development of scalable AI platforms and infrastructure while managing high-performing engineering teams. You will drive the design, delivery, and optimization of production-grade AI systems powering AI use cases across Meesho.

What You'll Do

• Lead, mentor, and grow a team of AI engineers — setting technical direction, raising the engineering bar, and owning execution and delivery end to end.
• Architect and scale Meesho's AI platform: cross-region model inference, multi-GPU fleet allocation and management, distributed training, and feature-engineering infrastructure.
• Drive inference optimization across the full stack — GPU kernel tuning, quantization (including outlier/tail-distribution handling), and memory/IO-bandwidth optimization — while building agents that codify and delegate known optimization procedures.
• Optimize open-weight models at both the model and inference-engine level — distillation, quantization, speculative decoding, KV-cache and serving-engine tuning.
• Scale data-science productivity through autonomous, agent-driven workflows spanning feature engineering, model training, and rollout.
• Push the frontier across MLOps, LLMOps, compute efficiency, and distributed ML systems.
• Partner with Product, Data Science, and Platform teams to turn AI capabilities into production impact for millions of users.
• Own the team's operating rhythm: hiring, performance management, sprint planning, and OKRs.

What You'll Need

• Bachelor's or Master's in Computer Science or a related field.
• 9+ years of software engineering experience, including 2+ years managing engineers.
• Strong hands‑on experience with the modern LLM inference stack — TensorRT-LLM, vLLM, SGLang — and with production, low‑latency model serving at scale.
• Depth in inference optimization: GPU kernel tuning, quantization, speculative decoding, KV‑cache and memory/IO optimization.
• CUDA / GPU programming experience is a strong plus.
• Experience with distributed training and the frameworks behind it — PyTorch FSDP, DeepSpeed, Megatron, or Ray.
• Experience running GPU fleets in production — Kubernetes (ideally GKE), GPU scheduling and allocation, and multi‑region/multi‑cluster deployment.
• Familiarity with building LLM-powered agents and agentic workflows, and a point of view on where autonomy can replace manual engineering toil.
• Experience with big‑data and streaming stacks — Spark, Flink, or similar.
• Proficiency in Python; systems‑level fluency (C++ / Go / Rust) for performance‑critical paths.
• Strong leadership, problem‑solving, and stakeholder‑management skills.
• Preferred Open‑source contributions to inference engines, training frameworks, or ML infra tooling.
• Experience managing GPU cost/efficiency (FinOps) for a large fleet on Cloud and Neo-Clouds.
• Track record building platforms for high‑scale consumer products (millions of users).
• Familiarity with observability and reliability for ML systems (SLOs, autoscaling, incident response).

Experience Level Mid Level