Top Tech Jobs & Startup Jobs in Mumbai

Leads Fractal’s AWS practice by owning P&L, driving strategic client growth, managing AWS alliances, and overseeing large-scale cloud transformation programs. The role combines executive relationship management, technology consulting, sales leadership, solution development, delivery governance, talent development, and financial management. The leader advises Fortune 500 clients on AWS, AI/ML, data, generative AI, security, modernization, and migration initiatives while building a high-performing distributed team and expanding AWS-led business.

Design and deliver production-grade Generative AI and LLM solutions, including RAG pipelines, agentic workflows, APIs, and reusable frameworks. Build, train, fine-tune, evaluate, and optimize AI systems for accuracy, latency, cost, reliability, and safety. Translate business needs into measurable AI outcomes, collaborate with technical and business stakeholders, contribute to architecture and proposals, and mentor junior team members.

Leads Fractal’s Azure practice, including strategy, team management, client engagement, service delivery, technical direction, budgeting, and business development. Drives Azure-based Generative AI and Agentic AI strategies, architectures, governance, accelerators, and enterprise implementations. Partners with Microsoft and clients to identify transformation opportunities, shape proposals, deliver executive presentations, and build organizational AI capabilities through innovation programs and training.

Design and deliver scalable Generative AI solutions using LLMs, RAG, AI agents, vector databases, and multimodal models. Lead cloud, MLOps, security, governance, and architecture strategies across AWS, Azure, and Google Cloud. Translate business needs into technical solutions, support client workshops and pre-sales, present strategies to executives, and mentor data science, ML engineering, and software teams.

Lead the engineering side of an agentic AI invoice-to-cash product, owning architecture, front end, services, data, infrastructure, platform decisions, delivery, quality, CI/CD, releases, and incident response. Manage and coach engineers while contributing code to complex areas. Partner with AI leadership and product management on system interfaces, feasibility, sequencing, trade-offs, and roadmap execution.

Develops GenAI and NLP models for text classification, sentiment analysis, entity recognition, translation, and semantic analysis. Responsibilities include text preprocessing, feature engineering, model training and evaluation, exploratory data analysis, algorithm optimization, and large-scale data processing. The role collaborates with engineering and domain teams to integrate NLP solutions, documents methodologies, and applies current machine learning advances to business problems.

Develops end-to-end generative AI and NLP solutions using LLMs, including chatbots, search, summarization, Document AI, and content generation. Conducts research, builds supporting libraries and frameworks, and applies prompt engineering, fine-tuning, vector databases, and cloud AI services. May also work with computer vision, audio, and video models. Collaborates cross-functionally throughout the software development lifecycle, contributing to design, testing, deployment, maintenance, code reviews, and technical roadmaps.

Design and implement end-to-end generative AI and LLM solutions, including NLP, computer vision, audio, and video applications. Research emerging AI techniques, develop supporting libraries and frameworks, and apply prompt engineering, fine-tuning, vector databases, and cloud AI services. Participate in software development, testing, deployment, maintenance, and code reviews while collaborating with cross-functional teams.

Owns end-to-end platform architecture across backend, frontend, AI services, data, cloud infrastructure, security, observability, and integrations. Designs scalable microservices using Java and Spring Boot, guides AI and frontend development, establishes CI/CD and architecture standards, and leads HRMS/ATS integrations. Represents engineering in client and pre-sales discussions, translates requirements into technical solutions, and mentors engineers across multiple teams.

Develop NLP and generative AI models for text classification, sentiment analysis, entity recognition, translation, and semantic analysis. Responsibilities include text preprocessing, feature engineering, model training and evaluation, exploratory data analysis, algorithm optimization, and large-scale data processing. Collaborate with engineering and domain teams to integrate solutions, document methodologies, and apply emerging NLP and machine learning techniques.