Top Tech Jobs & Startup Jobs in Mumbai

Designs and implements end-to-end generative AI and LLM solutions, researches emerging AI techniques, develops supporting libraries and frameworks, and participates in software delivery from design through maintenance. The role applies NLP, computer vision, audio, and multimodal AI methods; uses cloud and open-source platforms; contributes to code reviews and roadmaps; and collaborates with cross-functional teams.

Generate outbound demand for ANZ accounts through research, email, phone, and LinkedIn prospecting. Book qualified meetings and event attendees, support opportunity development, prepare client pitches, assist with RFPs and proposals, maintain CRM records, and accelerate pipeline follow-up. The role also supports partner events and requires ongoing learning about Fractal’s data and AI capabilities while working ANZ-aligned hours from Bengaluru.

This role involves planning and designing Azure infrastructure, developing cloud solutions, mentoring teams, and ensuring cloud security and compliance.

Owns deployment architecture and installation of an agentic invoice-to-cash platform in client Azure environments. Responsibilities include Databricks governance, release sequencing, reusable platform utilities, ingestion strategy, CI/CD, incident command, hypercare, deployment playbooks, validation standards, and coaching junior engineers. The role requires client-facing technical leadership, production PostgreSQL expertise, strong Python and SQL, and experience deploying data platforms into environments outside the company’s control.

Owns technical direction for enterprise agentic AI solutions across application, cloud, data, and AI layers. Leads architecture decisions, deployment standards, security reviews, reusable infrastructure, CI/CD practices, and production monitoring. Mentors Forward Deployed Engineers toward independent delivery, guides design and code reviews, prototypes high-risk components, and resolves critical blockers. The role emphasizes technical leadership, scalable deployment capability, cloud cost discipline, agent evaluation, guardrails, and operational reliability rather than sustained feature development.

The Senior Azure Data Engineer will design, develop, and maintain data infrastructure and pipelines, ensuring data quality, integrity, and alignment with business objectives. Responsibilities include collaborating with teams and establishing best practices for data engineering.

Lead the Business Intelligence center of excellence by managing teams, building BI practices, and optimizing BI solutions using various tools.

Advise clients on developing and implementing data governance strategies. Design policies, frameworks, and practices for data quality, privacy, metadata management, and security. Deliver governance projects, build capability with frameworks and accelerators, and promote governance awareness across stakeholders and committees.

Design, build, and maintain Azure-based data infrastructure and pipelines. Implement data models and schemas, ensure data quality, optimize distributed storage and processing (Databricks/PySpark), and establish engineering best practices while partnering with cross-functional teams.

Work with enterprise customers to design, build, and deploy production-grade AI solutions on the Cogentiq platform. Implement integrations with enterprise systems, develop connectors, backend services, and microservices, ensure scalability, security and observability, troubleshoot deployments, and turn deployment learnings into reusable platform capabilities.