Top Artificial Intelligence Jobs in Pune

Design, build, and maintain production-quality full-stack software, APIs, backend services, automation, cloud-native applications, integrations, and CI/CD pipelines. Develop AI-enabled solutions using LLMs, RAG, and agentic workflows. Apply strong practices in testing, observability, security, reliability, and maintainability while contributing to technical design and solving ambiguous engineering problems.

Leads enterprise IT security and non-human identity governance programs, including identity inventory, risk classification, CI/CD and container identity, secrets management, AI agent governance, API key controls, MCP access, audit trails, shadow AI discovery, incident response, compliance, executive reporting, budgeting, and cross-department security strategy.

Build and optimize scalable full-stack web applications using React, Python, and modern JavaScript or TypeScript. Deploy cloud-native applications, preferably on Azure, integrate LLM and agentic AI services, work with APIs and microservices, and support Docker-based CI/CD pipelines. The role also emphasizes performance, observability, high-throughput data handling, and reliable production deployments.

Lead Alpaca’s global Trading API customer experience organization, including General and VIP Support. Build a follow-the-sun coverage model, establish service standards and KPIs, improve support through data, AI, automation, and self-service, and develop high-performing teams. Partner with Product, Engineering, Trading, Operations, Compliance, and Sales to resolve recurring issues, improve customer workflows, and support institutional trading customers.

Leads the design, development, maintenance, testing, optimization, and troubleshooting of complex software applications. Collaborates with cross-functional teams, documents technical requirements, resolves IT issues, prepares data, supports end users, and applies mathematical and statistical techniques. The role also promotes responsible AI tool usage, validates AI-generated code, and designs agentic workflows to improve engineering productivity.

Supports customers through live chat by troubleshooting wireless internet products and services, resolving issues, and delivering positive customer experiences. The role requires energetic, meaningful customer engagement and focuses on helping clients’ customers while contributing to customer experience insights and digital support operations.

MBA summer associates join Roland Berger for an 8–12-week internship, contributing to real client projects with consulting teams across global offices. Responsibilities involve strategic work, analytical and creative problem-solving, teamwork, entrepreneurial thinking, and applying AI-based solutions and data skills to complex business challenges. High-performing interns may receive full-time offers.

Own and lead the company’s end-to-end legal function, including drafting and negotiating commercial agreements, advising on contractual risks, managing vendors and external counsel, supporting employment and equity matters, and handling fundraising, governance, IP, privacy, compliance, and regulatory issues. The role requires strong US commercial contract expertise and experience supporting US-based companies, ideally in pharma, life sciences, or healthcare.

Designs scalable, secure Enterprise AI and GenAI solutions across manufacturing, MedTech, commercial, and procurement domains. Responsibilities include architecture blueprints, system integrations, AI governance, responsible AI controls, solution assurance, stakeholder collaboration, vendor delivery oversight, and embedded assistant initiatives. The role guides AI use-case discovery, deployment, adoption, monitoring, and continuous improvement while ensuring regulatory, privacy, cybersecurity, auditability, and operational-readiness requirements are met.

Lead enterprise AI architecture, governance, standards and platform selection. Define AI/agent patterns (A2A, MCP), integration and security controls, govern Architecture Review Board decisions, produce reference architectures and playbooks, and enable global adoption across cloud, data, ERP/CRM and regulated manufacturing/MedTech environments.

Develop system software and infrastructure for deploying, benchmarking, and qualifying local AI workloads across Linux and Windows GPU systems. Build CI pipelines, model management services, databases, data pipelines, dashboards, telemetry, scheduling systems, and autonomous infrastructure agents. Collaborate with inference and application teams to improve reproducibility, diagnose system issues, detect regressions, and optimize performance.

Designs and oversees enterprise software architecture, development, testing, implementation, and technical documentation. Partners with stakeholders and Product teams to define requirements, evaluate technologies, create scalable solutions, review code, support application integrations, and guide development teams. The role also coordinates technology projects, training, system improvements, security, quality, and extensibility while providing technical support for case and client efforts.

Design, develop, and maintain scalable enterprise applications using Java, Spring Boot, microservices, APIs, and cloud-native technologies. Collaborate with cross-functional teams to deliver secure, reliable, high-performance solutions for business-critical needs.

Develop, train, fine-tune, evaluate, and deploy machine learning models using large datasets. Responsibilities include data preprocessing, feature engineering, deep learning, NLP and LLM research, predictive analytics, production API integration, experimentation, and model optimization. The role collaborates with software engineers, supports MLOps practices, and evaluates model accuracy, efficiency, latency, and performance.

Develop and ship Yahoo Mail mobile features for Android, owning projects from technical design through deployment, monitoring, and improvement. Build scalable solutions using Kotlin, Java, Android frameworks, Jetpack Compose, and React Native; integrate APIs; address performance, reliability, and usability challenges; conduct code reviews; collaborate cross-functionally; mentor teammates; and use AI development tools to improve engineering productivity while maintaining quality and security.

Own enterprise AI customer deployments from discovery and product scoping through delivery, adoption, and value realization. Translate customer workflows into product requirements, technical solutions, deployment roadmaps, and measurable outcomes. Partner with engineering, sales, customer success, finance, legal, security, and operations while evaluating AI trade-offs, business value, and production readiness. Identify reusable customer needs and help establish scalable product, operating, and deployment playbooks.

Create commercial-quality graphic assets for advertising and video production across mobile games, apps, and social platforms. Responsibilities include designing UI elements and visual materials, generating and refining assets with AI tools, maintaining consistency across creative variations, preparing layered files for animation, adapting designs for multiple formats, and collaborating with creative and production teams.

Leads application engineering work focused on high-volume security vulnerability remediation, dependency upgrades, OWASP fixes, and agentic coding workflows. Works rapidly across unfamiliar codebases, uses GitHub Actions and disciplined pull-request practices, and delivers merge-ready changes. Serves as the technical lead embedded with client product teams, runs daily standups, teaches team members, and remains accountable for delivery and capability enablement.

Leads client-embedded application engineering teams, remediating security vulnerabilities, upgrading dependencies, resolving breaking changes, and applying OWASP code fixes. Uses agentic coding workflows to generate and correct pull requests, works rapidly across unfamiliar codebases, and applies GitHub Actions and disciplined review practices. Runs daily standups, teaches client teams, and owns technical delivery and team output.

Leads client-embedded software teams in remediating security vulnerabilities, upgrading dependencies, resolving breaking changes, and applying OWASP code fixes. Uses agentic coding workflows to create and review merge-ready pull requests, works rapidly in unfamiliar codebases, and manages GitHub Actions and pull-request practices. Runs daily standups, teaches client teams, and remains accountable for technical delivery and team output.

Develop R automation and AI solutions supporting pharmaceutical clinical trials. Interpret requirements, identify workflow improvements, build proof-of-concept tools using R, Shiny, and LLM-supported coding, and mature successful prototypes into validated, documented, reusable solutions. Collaborate with statisticians, programmers, data scientists, and automation leads while ensuring compliance with clinical development standards, including testing, traceability, audit trails, version control, and regulated delivery expectations.

Lead pre-sales and technical delivery for Microsoft Industry Solutions, mapping customer needs to Microsoft Cloud and AI solutions. Drive project planning, risk mitigation, stakeholder engagement, IP reuse, and business development while mentoring teams and ensuring operational compliance.

Design, implement, review, and validate production-grade Rust backend systems for AI training projects. Responsibilities include API development, persistence, asynchronous processing, concurrency, performance optimization, reliability testing, architecture assessment, debugging, and creating reproducible environments with databases, dependencies, fixtures, and containers. The role requires clear technical documentation, evaluation of failure scenarios and race conditions, and consistent delivery of high-quality implementation artifacts.

Design, build, and scale production AI agent workflows using AWS Bedrock AgentCore, Step Functions, Claude, MCP, RAG, and guardrails. Develop Python/FastAPI backends, agent-facing interfaces, document-processing pipelines, enterprise integrations, and AWS infrastructure. Implement observability, evaluations, security controls, human approval workflows, and CI/CD. Work directly with enterprise customers and nontechnical stakeholders to deliver end-to-end AI solutions with minimal guidance.

Leads enterprise AI architecture and transformation across hybrid and multi-cloud infrastructure environments. Designs Generative AI, AIOps, automation, governance, security, and self-healing infrastructure solutions using platforms such as Azure, AWS, and GCP. Develops RAG architectures, AI assistants, and operational workflows integrated with ServiceNow and enterprise systems. Advises executive stakeholders, leads large transformation programs, and supports solutioning, presales, governance, and customer-facing consulting.