Top Artificial Intelligence Jobs in Pune

Design and deliver enterprise AI solutions on SAP BTP: build/deploy ML models (AI Core/Launchpad), integrate Joule across SAP products, prototype AI use cases, create intelligent workflows with SAP Build Process Automation, define AI architecture, MLOps pipelines, and multi-cloud integration patterns aligned with Clean Core.

Build and productionize LLM-powered agents, workflows, and RAG systems. Apply prompt engineering, embeddings, fine-tuning, and traditional ML to automate tasks and improve products. Mentor teammates and help design scalable, production-grade AI infrastructure while staying current on LLM advances.

Join a remote team as a Lead Data Scientist focusing on building Generative AI applications. Responsibilities include developing applications, implementing pipelines, and performing model tuning.

As a Senior Full Stack Developer, you will design and build end-to-end features across backend and frontend using .NET and React, collaborate on system architecture, and integrate AI capabilities.

The AI Platform Engineer leads the development of production AI agents and components, collaborates on AI implementations, and maintains AI systems for reliability and observability.

The AI Engineer will maintain and enhance AI services on the Sootra platform, optimizing pipelines, managing microservices, and developing feedback systems to improve AI performance.

The Senior Product Manager will lead AI product strategy at CoinMarketCap, focusing on user needs and data analysis to drive product development.

Build and scale a full-stack Next.js application tracking PRs, CI health, test parity, and benchmarks across AI accelerator open-source projects. Integrate GitHub APIs and webhooks, design PR/metrics schemas, visualize results, and produce technical digests and reports on cross-accelerator parity and performance trends.

Build and ship AI-powered features for fashion, beauty, and home using large-scale product, image, and consumer data. Prototype with LLMs, agents, multimodal and CV models, run experiments, measure impact, and take models end-to-end from hypothesis to production while collaborating with product, design, and business teams.

Design and implement the core AI layer for enterprise compliance workflows: document extraction, retrieval, RAG, agentic task execution, evaluation pipelines, and human-reviewable AI features to improve accuracy, traceability, and workflow automation.

Design and build the core intelligence layer for enterprise AI workflows: document extraction, retrieval, ranking, generation, evaluation pipelines, agentic task execution, and integration into a polished product while prioritizing accuracy, traceability, and human-in-the-loop review.

The ServiceNow Solution Architect - AI role involves leading and mentoring a team, designing and deploying AI-driven applications, managing application development, and integrating solutions into ServiceNow modules. Responsibilities include coordinating with stakeholders, troubleshooting, and ensuring adherence to technical standards.

Build and maintain Python/FastAPI backend services and React frontends, design and consume REST APIs, work with relational databases, and implement/debug AI-enabled features including vector DBs, embeddings, semantic search, and RAG workflows. Improve existing codebases, collaborate with product and design, participate in testing, deployment, and monitoring, and ensure performance, security, and maintainability.

Design, develop, and deploy advanced AI/ML models (including LLMs and agentic systems) to improve search, forecasting, text mining, anomaly detection and root-cause analysis. Optimize models and ML pipelines for performance, scalability, and resource efficiency; work with big-data frameworks and vector/search systems.

Design and implement end-to-end generative AI solutions using LLMs and multimodal models. Build libraries, tools, and production integrations; perform research, code reviews, testing, deployment, and cross-functional collaboration. Focus areas include NLP, computer vision/audio, prompt engineering, model fine-tuning, and cloud deployment.

The AI Tech Lead will strategize and implement AI solutions across the bank, driving business efficiency and enhancing customer experiences through innovative AI and machine learning applications.

The IT Operations Engineer will manage AI and Data platforms, ensure operational health, lead incident resolution, and automate tasks while collaborating with engineering teams.

Design, develop, and improve software solutions while collaborating with cross-functional teams and adhering to security policies and coding practices.

The Lead Engineer - Applied AI will design, develop, and improve scalable software solutions using advanced AI frameworks and cloud technologies. Responsibilities include code quality assurance, team collaboration, risk management, and aligning projects with business objectives.

The Staff Engineer-Applied AI role involves designing, developing, and improving software solutions, leading GenAI and Agentic AI projects, collaborating with teams, and ensuring code quality and security compliance.

The Senior Software Engineer will develop software tools for Red Hat's partners, enhance integration and feature development, automate deployments and testing, and work with advanced hardware and AI tools.

The role involves developing enterprise applications using Java and Spring, integrating AI features, mentoring junior developers, and collaborating with cross-functional teams.

As a Senior Technical Product Manager, lead the development of Autodesk's Knowledge Retrieval Platform, improving discoverability and AI functionality across products. Manage product lifecycle, promote customer value through rapid prototyping, and work with teams to articulate platform value. Define and track relevant quality metrics and manage the product roadmap.

As an AI DevOps Engineer, you will lead AI/ML solution delivery, oversee CI/CD processes, and mentor engineers while ensuring security and scalability of cloud infrastructures.

The role involves evaluating AI outputs, reviewing text, analyzing multimedia, and providing culturally relevant content in Kannada while ensuring quality and accuracy.