Top Tech Jobs & Startup Jobs in Mumbai

Embed with client engineering teams to translate requirements into production software. Build Python backend services, APIs, integrations, RAG pipelines, tool-calling agents, and LLM workflows. Deliver platform improvements and AI use cases while applying testing, CI/CD, monitoring, security, and reliability practices. Communicate technical decisions and risks, document solutions, and transfer operational knowledge to client teams.

Build and deploy enterprise Generative AI applications using LLMs, RAG pipelines, vector databases, multimodal models, and autonomous agents. Develop prompt flows, benchmark and fine-tune models, implement MLOps practices, deploy solutions across major cloud platforms, and integrate AI capabilities into APIs and microservices. Collaborate with consultants, data scientists, engineers, architects, and customers to deliver secure, scalable, compliant, and cost-effective GenAI solutions.

Administer and enhance Meraki and UniFi network infrastructure across international offices, including firewalls, switches, access points, cabling, and office deployments. Manage Microsoft 365, Entra ID, Intune, and Azure environments; provide advanced network and application support; automate administration using PowerShell, Python, and Microsoft Graph API; support data migrations, technical documentation, and IT integration during acquisitions. Occasional international travel is required.

Provide global Level 1 and Level 2 technical support through ticketing, phone, Teams, and on-site channels. Diagnose hardware, software, network, account, and access issues; configure Windows and Mac workstations; manage devices, inventory, and lifecycle activities; document resolutions; meet ITSM and SLA requirements; support VIP users; and collaborate with international IT teams in a 24x7 rotational shift environment.

Collects, curates, classifies, and organizes strategic knowledge assets from internal and external sources. Maintains metadata, taxonomies, repository hygiene, version control, and data quality standards. Uses AI-enabled tools such as NLP, semantic search, document classification, and automated tagging to improve knowledge processing and retrieval. Supports consulting teams with content access, reporting, dashboards, governance monitoring, and continuous improvement initiatives.

Architect and standardize multi-cloud DevOps and platform foundations for AI products. Lead CI/CD, Kubernetes, infrastructure automation, observability, security, reliability, scalability, and cost governance across teams. Serve as the escalation point for complex infrastructure issues, drive incident response and resilience practices, improve developer workflows, review architectural designs, build foundational tooling, and mentor senior engineers while influencing organization-wide technical strategy.

The DevOps Engineer supports consulting engagements, SaaS product development, and data-focused projects. Responsibilities include managing cloud architecture and services, optimizing costs and access, containerizing and orchestrating applications with Docker and Kubernetes, developing Python automation tools and microservices, implementing CI/CD pipelines, and contributing to scalable technology, architecture, and governance decisions.

Leads engineering teams building AI and generative AI SaaS platforms. Owns technical roadmaps, cloud architecture, scalability, security, CI/CD, and operational excellence while contributing targeted code and infrastructure improvements. Partners with product, data science, research, and operations teams to deliver reliable customer-facing systems. Responsibilities include hiring, coaching, architectural reviews, technical leadership, product-engineering alignment, and communicating AI trade-offs to clients and stakeholders.

Develop and optimize Python back-end services, microservices, and data-centric applications for AI-powered SaaS solutions. Integrate and optimize AI/ML models, manage PostgreSQL and MongoDB databases, deploy containerized applications with Docker and Kubernetes, and manage cloud infrastructure using Terraform and Helm across GCP, AWS, and Azure. Collaborate with DevOps, data scientists, and data engineers while contributing to software architecture, testing, CI/CD, and engineering team mentorship.

Designs and delivers production-grade AI and Generative AI platforms using Python, distributed systems, microservices, and cloud-native technologies. Owns backend architecture, deploys and scales machine learning models, manages infrastructure with Terraform and Helm, and leads Docker and Kubernetes practices. Ensures database performance, observability, reliability, and incident response. Provides technical leadership on client engagements, mentors engineers, influences strategy, and translates business requirements into scalable technical solutions.