Top Artificial Intelligence Jobs in Pune

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.

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.

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.

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.

Lead enterprise customers in deploying Generative AI solutions, architect production systems, and mentor on AI Factory deployments while optimizing MLOps and inference processes.

Lead design and deployment of Responsible AI solutions, ensure ethical and regulatory alignment, own AI governance, mentor teams, collaborate cross-functionally, and monitor AI impact for compliance.

The BIA VP - Finance and Treasury is responsible for auditing, risk management, strategy setting, and stakeholder communication in a banking environment.

Support and enhance ADI's global compliance program aligned to enterprise risk and ISO 37301. Monitor regulatory developments, update policies, execute risk‑based monitoring and testing, manage investigations and remediation, support audits, develop training and communications, track metrics, and collaborate with Legal, HR, Finance, IT, and Operations to drive continuous improvement.

Lead and support execution of ADI's global compliance programs: risk‑based monitoring, policy management, testing, investigations, training, ISO 37301 alignment, audits, remediation, and cross‑functional stakeholder coordination.

Build and integrate agentic and generative AI solutions: implement RAG pipelines, integrate LLMs and agent frameworks, write production-quality Python, apply TDD, build data pipelines and visualizations, and collaborate in Agile consulting engagements to deliver client-facing AI products.

Lead design and delivery of agentic and generative AI systems including multi-agent orchestration, RAG pipelines, LLM integration, and AI-coding agent workflows. Provide technical leadership on client engagements, mentor engineers, perform EDA and statistical analysis with Python, and enforce engineering standards, TDD and scalable system design while contributing to practice development.