Backend Engineer - AI/ML Platform (Senior / Staff-ready)

This role is for one of the Weekday's clients Salary range: Rs 1500000 - Rs 2500000 (ie INR 15-25 LPA) Min Experience: 6 years Location: Mumbai, Pune JobType: full-time We are seeking a senior-level backend/platform engineer to build and operate ML-backed systems that power large-scale, production-grade AI applications.
This role sits at the intersection of backend engineering and applied machine learning, with ownership spanning system design, runtime orchestration, and end-to-end reliability.
You will work closely with ML teams to translate models and prompts into robust, observable, and cost-efficient production systems.
The role is based in Mumbai initially, with a potential transition to Bangalore after March 2026, and requires mandatory in-office collaboration.
Key Responsibilities Design, build, and operate scalable backend systems that support ML-driven applications in production Own runtime orchestration, including session and state management, retrieval and memory pipelines such as chunking, embeddings, indexing, vector search, re-ranking, caching, freshness, and deletion Productionize ML workflows by defining feature and metadata services, model integration contracts, and ensuring offline and online parity Implement evaluation and instrumentation frameworks to continuously measure system and model performance Drive system performance, reliability, and cost efficiency across latency, throughput, infrastructure usage, and token economics Build observability-first platforms with strong tracing, metrics, logging, guardrails, and fallback mechanisms Partner closely with applied ML teams on prompt schemas, tool routing, evaluation datasets, and safe, incremental releases Take full ownership of systems from design to deployment, monitoring, and ongoing improvements, shipping independently and responsibly What Makes You a Great Fit 6–10 years of experience in backend or platform engineering, operating at a senior or staff-level scope Strong background in building and maintaining distributed, production-grade systems at scale Hands-on exposure to ML-adjacent systems such as model serving, retrieval pipelines, orchestration layers, and inference workflows Demonstrated ownership of reliability, performance optimization, and cost control in live production environments Comfortable working in-office and based in Mumbai or Bangalore, with flexibility for a future location transition A proactive mindset with the ability to work independently, make sound technical decisions, and own outcomes end-to-end Bonus points for experience building greenfield AI platforms, working with US enterprise clients, or already being based in Mumbai