Top Artificial Intelligence Jobs in Pune

Lead LLM-focused data science work: analyze large datasets, build statistical models, design and deploy LLM/agentic applications, perform prompt engineering and model fine-tuning (RAG), and collaborate with global teams to deliver AI-driven business solutions.

Review AI-escalated risk cases (KYC, ATO, 2FA, withdrawals), make pass/block/escalate decisions, label outcomes with root-cause annotations to train ROCA, maintain SLAs and accuracy, update SOPs, and support model calibration and BPO onboarding.

Responsible for functional and API testing of platform products, designing and executing end-to-end tests across frontend, backend, strategy, and algorithms. Validate personalized user experiences, improve test coverage and QA processes, and drive adoption of AI-assisted test generation and automation. Collaborate with Product, Engineering, Algorithm, and Strategy teams to identify issues and ensure quality.

Early-career DevOps role focusing on Kubernetes and AWS operations, embedding security into the development lifecycle, automating processes, and implementing CI/CD solutions. Remote, fixed-term accelerator program for students and recent graduates.

Design and implement end-to-end machine learning solutions: analyze use cases, build statistical and ML models, prepare and enrich data, implement scalable PySpark models in Databricks, and collaborate with product and engineering to productionize analytics for personalization and business insights.

Lead design and architecture of Generative AI solutions on Azure and OpenAI, build end-to-end data pipelines and cloud infrastructure, produce solution blueprints, collaborate with stakeholders, and implement data preprocessing, API deployment, monitoring, and analytics delivery.

Design and architect AI/GenAI solutions on GCP; create architecture diagrams; develop, deploy, and optimize ML models; preprocess and manage large datasets; provide technical guidance to engineering teams; and present solutions to clients.

Design, fine-tune, and deploy generative AI models (LLMs, diffusion, VAEs). Build data pipelines and APIs, integrate AI into production, optimize model performance and latency, and collaborate with cross-functional teams to deliver AI-powered solutions.

Lead AI strategy and implement GenAI, agentic AI, and automation to modernize legacy systems, integrate AI into engineering lifecycle, and build production-grade, scalable AI solutions with cloud, containerization, MLOps, and data pipeline best practices.

Design, develop, fine-tune, and deploy generative AI models (LLMs, diffusion, VAEs). Build data pipelines, APIs, and integrate AI into production while improving performance and collaborating with cross-functional teams.

Design, build, and maintain AI platform and ML pipelines by assembling LLMs and agentic workflows, integrating assistants with systems, prototyping in low-code and code, writing tests and CI/CD, and iterating with stakeholders on domusAI, domiAI, domusDocs and multi-agent frameworks.

Design, build, and scale production Generative AI systems: multi-agent workflows, advanced RAG pipelines, model fine-tuning and quantization, LLM integration and swapping, high-performance FastAPI backends, vector search and retrieval, containerized deployment, and monitoring for latency, cost, and reliability.

Build and deploy production-grade generative AI applications: design multi-agent systems and LangGraph workflows, implement advanced RAG with vector DBs, fine-tune and host LLMs, develop scalable FastAPI backends, optimize latency/cost, and containerize services for production.

Design, build, and maintain production-ready full-stack applications combining React frontends with Java/Python backends. Integrate Generative and Agentic AI workflows, implement CI/CD, deploy cloud-native services on Kubernetes (GCP/Azure), manage relational and NoSQL databases, apply automated testing, observability, and troubleshoot production systems while collaborating across DevOps, QA, and Product teams.

Design, build, and operationalize production-grade agentic AI solutions (RAG, multi-agent workflows, human-in-the-loop). Deliver client engagements, create reusable accelerators, ensure reliability/security/observability, and drive technical standards, documentation, testing, and measurable business outcomes across distributed teams.

Deploy and operationalize AI-powered workflows and integrations (notably within ServiceNow) for clients. Build prototypes, integrate LLMs and AI services, develop microservices and automation, troubleshoot and optimize production systems, and contribute reusable assets to NewRocket's AI platforms while working directly with customers and cross-functional teams.

Design, develop, and implement AI, GenAI and automation solutions for IT/business processes. Build reusable automation scripts and workflows, train ML models for anomaly detection and predictive maintenance, work with large operational datasets, integrate AI into workflows, develop microapps for OEM marketplaces, troubleshoot automation systems, and document processes while evaluating tools and mentoring team members.

Develop and maintain AI-driven web applications using the MERN stack; integrate ML/AI models and third‑party AI services; build scalable Node/Express APIs; optimize performance and frontend UI with React; collaborate with data scientists to productionize models; participate in CI/CD, code reviews, and technical planning.

Lead CRM strategy and MarTech solutioning for enterprise clients: win and run large RFPs, design customer lifecycle, segmentation, personalization and journey orchestration, select and integrate CEP/CDP/CRM/data platforms, present to executives, and mentor cross-functional teams in a consulting or agency environment.

Lead CRM strategy and MarTech solutioning for enterprise clients: design customer lifecycle, segmentation, personalization, and cross-channel journey orchestration; architect integrations across CEPs, CDPs, CRM systems and data warehouses; win large RFPs; present to executives; and mentor cross-functional teams.

Lead innovation and process improvements in testing, integrate AI into QA practices, perform automation scripting, and mentor Quality Engineers.

Drive architectural decisions for a large-scale AI-first application platform, ensuring high-impact and reliable solutions while mentoring engineers and cultivating a collaborative culture.

Annotate and quality-review multimedia data (video, images, metadata) using detailed labeling guidelines. Perform self-QA, flag ambiguities, join calibration sessions, track recurring issues, support sampling and audits, and coordinate with stakeholders to meet throughput and quality targets. Work is remote and requires Assamese language proficiency.

Annotate and QA multimedia (video, images, metadata) using detailed labeling rules, perform self- and second-pass reviews, participate in calibration, document edge cases, and coordinate with stakeholders to meet quality and throughput targets.

Annotate and review multimedia data (video, images, metadata) using strict labeling rules, perform self-QA and second-pass reviews, flag ambiguous cases, participate in calibration, track recurring issues, and coordinate with stakeholders to meet quality and throughput targets. Work is remote and requires Bodo language proficiency.