Top Artificial Intelligence Jobs in Pune

The Principal Software Engineer will architect AI platforms, mentor the team, manage projects, and ensure alignment with architectural guidelines.

The Senior Specialist will define technical requirements for Mastercard's products, manage ISO message specifications, and collaborate on product strategy and API design.

Work with internal and client teams to analyze business problems, design and implement technical features using SQL, Python, and cloud platforms. Contribute to development, testing, and deployment using modern methodologies (agile, QA, unit testing). Support project implementation plans, translate requirements into technical designs, and collaborate across teams to deliver scalable Gen AI and analytics solutions.

The Lead AI Scientist will design and optimize LLM architectures, fine-tune models, develop AI systems, mentor junior members, and collaborate with clients and teams on AI solutions.

Design, build, and operate agentic LLM-powered workflows, autonomous agents, and RAG/vector retrieval systems. Own end-to-end delivery including CI/CD, IaC, observability, DevSecOps, and Salesforce integrations to productionize enterprise AI for GTM applications.

Design, develop, and deploy scalable Java-based microservices (Spring Boot) in CI/CD-enabled cloud environments. Build event-driven, real-time systems with appropriate data persistence (RDBMS/NoSQL). Leverage AI/ML and GenAI for solutions and PoCs, ensure security/compliance, drive code quality, mentor engineers, and collaborate across teams to deliver projects on schedule.

Lead AI/ML engineering vision and roadmap for healthcare and life sciences. Oversee multiple client engagements, design and deploy scalable production-grade AI solutions (ML, NLP, deep learning, computer vision, LLMs), ensure regulatory readiness, responsible AI practices, and drive adoption and value realization while managing executive client relationships and expanding AI adoption.

Develop and implement digital twin architectures for patient modeling, research AI innovations, mentor junior team members, and contribute to client solutions.

Lead the development of generative AI systems, overseeing multi-agent AI architectures, machine learning pipelines, and implementing responsible AI practices. Drive innovation in AI applications using various frameworks and databases while managing cross-functional teams.

Lead technology vision and architecture for enterprise projects; design cloud-native, data-driven and Generative AI solutions; ensure scalability, security, governance, and engineering excellence; run architecture reviews, POCs, and implementations; evaluate emerging technologies; influence clients via workshops and executive engagements; mentor architects and distributed engineering teams.

Perform static and dynamic malware analysis, develop automation and detection signatures, conduct IOC/reputation analysis, validate AI/ML model outputs, and produce threat research and tooling to protect and scale Zscaler's platform.

Build end-to-end full-stack AI features on a Ruby on Rails backend and React frontend, design and run experiments (A/B tests and AI evaluations), implement AI infrastructure for reliable LLM inference, and iterate quickly to scale production-ready LLM-powered products.

Design and implement Generative AI solutions to improve operational efficiency. Collaborate with teams to identify opportunities and ensure data governance.

Lead the development of AI-powered customer support solutions, guiding a team to build scalable, reliable, and secure systems using LLMs and third-party integrations.

Lead and grow engineering teams to design, build, and operate scalable data and AI platforms. Own end-to-end delivery, architecture, and operational excellence for data pipelines, AI-enabled services, and platform capabilities while ensuring security, reliability, governance, and cross-functional alignment.

Manage and grow an India-based AI Development team to deliver enterprise agent applications. Translate product priorities into sprints, partner with the Director of AI on roadmap and technical execution, establish async-first delivery rhythms across US/India, handle India operations (hiring, performance, compensation), coach on modern programming practices, and unblock work through cross-team relationships.

Seeking a Senior Data Scientist skilled in GenAI/LLMs to design and implement solutions for enterprise, conducting research and mentoring others.

Lead design, build and maintenance of data architectures, pipelines, warehouses and lakes; enable ML lifecycle by preparing governed datasets, collaborating with data scientists, and driving data governance, lineage, access controls and analytics-ready schema design.

Design and build production-grade AI-powered, agentic applications using LLMs, RAG, MCP and agent frameworks. Implement embeddings, vector stores, semantic search, autonomous agents, cloud-based scalable architectures, monitoring, and mentor developers while collaborating with product and data teams.

The Senior Data Scientist will architect real-time fraud detection systems, process large data sets, mentor teams, communicate findings, and innovate using AI technologies for effective risk management.

The AI Lead Engineer will design scalable AI and GenAI systems, lead complex solution designs, and ensure production-grade implementation of AI solutions without formal management.

Lead the design and implementation of scalable AI systems, providing technical guidance and solving complex problems, ensuring systems' robustness and efficiency.

Lead development and deployment of ML/AI solutions: build models (classification, prediction, anomaly detection, NLP), prototype ML products, prepare and pipeline data, collaborate with product and engineering, deliver insights, and mentor team members.

Design, build, and deploy GenAI/LLM-powered solutions (chatbots, summarization, document processing, knowledge assistants). Implement prompt engineering, data preprocessing, embeddings, RAG pipelines, and vector DB integrations. Integrate models via REST APIs, collaborate with product and engineering teams, monitor model performance, and ensure responsible AI practices and production-ready deployment.

Lead development and production deployment of AI/ML models focused on personalization, recommendations, segmentation, and predictive analytics. Collaborate with data engineering and development teams to ensure data readiness, integrate models into production (real-time systems like Kafka), apply AIOps to monitor performance, and mentor an AI/ML team.