Top Tech Jobs & Startup Jobs in Mumbai

Owns the enterprise architecture and hands-on implementation of Coursera’s agentic AI foundation. Designs agent orchestration, context and semantic architectures, governance, security, CI/CD automation, cost optimization, integrations, observability, and production standards. Enables business teams to build reliable AI-native workflows at scale while partnering with Engineering, IT, Data, Security, and business pods. The role also includes hiring, coaching, technical leadership development, and defining operating models and adoption metrics.

Process global invoices, manage vendor onboarding and records, support month-end accruals, audit employee expenses, administer travel and corporate card programs, resolve payment and policy issues, analyze travel and expense data, and assist with process improvements and automation.

Build and operate production LLM systems, including prompt and pipeline versioning, evaluations, monitoring, observability, RAG and vector-store infrastructure, safety guardrails, and cost governance. Develop CI/CD and operational tooling for non-deterministic AI outputs, manage reliability and compliance requirements, and collaborate with engineering and product teams to turn AI prototypes into scalable, secure, cost-effective production systems.

Own enterprise AI customer deployments from discovery and product scoping through delivery, adoption, and value realization. Translate customer workflows into product requirements, technical solutions, deployment roadmaps, and measurable outcomes. Partner with engineering, sales, customer success, finance, legal, security, and operations while evaluating AI trade-offs, business value, and production readiness. Identify reusable customer needs and help establish scalable product, operating, and deployment playbooks.

Build and scale production-grade agentic AI infrastructure and platform capabilities. Lead architecture, technical design, reliability, scalability, data privacy, and end-to-end delivery. Collaborate with product and innovation teams to define customer solutions, mentor engineers, improve developer experience, and resolve complex technical issues. The role requires backend engineering, cloud infrastructure, APIs, databases, automated testing, infrastructure as code, and CI/CD expertise.

Build applied AI systems and prototypes using LLMs, RAG pipelines, vector databases, agentic workflows, structured extraction, and custom models. Design evaluation frameworks, measure accuracy and grounding, analyze errors, and iterate on solutions. Work with large structured and unstructured datasets using Python, SQL, and cloud data platforms. Partner with product, data, engineering, and business teams to translate ambiguous problems into measurable AI solutions and document architectures, prompts, runbooks, and results.

Build and deploy AI-powered customer solutions across discovery, prototyping, and production. Responsibilities include designing secure multi-tenant and hybrid architectures, integrating identity and access management, encryption, networking, data engineering, CI/CD, observability, and production support. The role partners directly with enterprise customers, executive sponsors, and cross-functional teams to solve ambiguous problems, demonstrate prototypes, and standardize successful solutions. Regular domestic and occasional international travel is required.