Top Tech Jobs & Startup Jobs in Pune, MH

Design, build, deploy, and operate enterprise AI, machine learning, generative AI, and agentic AI systems. Productionize prototypes into scalable platforms, develop end-to-end ML pipelines and LLM applications using RAG and vector databases, and implement MLOps and AgenticOps practices. Architect cloud-native services with Kubernetes and microservices, optimize reliability and performance, and ensure security, privacy, compliance, governance, and responsible AI standards. Collaborate with technical and business stakeholders on reusable AI capabilities and strategic roadmaps.

Leads quality engineering across complex projects, including test strategy, planning, automation, validation, integration testing, and release readiness. Designs tests for APIs, systems, services, data flows, and interfaces using Playwright, Cypress, Gatling, and BlazeMeter. Partners with product and engineering teams to clarify requirements, troubleshoot technical issues, manage risks, and improve workflows. Communicates quality insights to stakeholders, mentors colleagues, and promotes scalable quality practices.

Designs and implements automated test frameworks and Java-based automation for API, UI, integration, regression, and end-to-end testing. Integrates tests into Jenkins CI/CD pipelines, performs defect and root-cause analysis, defines test strategies, and collaborates across development, product, and DevOps teams. The role also involves Agile participation, quality engineering improvements, and mentoring junior engineers.

Deploys as a principal engineer across Mastercard Services teams to write production code, resolve technical bottlenecks, accelerate delivery, and establish reusable capabilities. Designs and deploys AI assistants, agents, and multi-agent workflows using LLMs, RAG, evaluation, observability, and governance. Coaches teams on AI-first software development, transfers knowledge, develops reusable patterns, and partners with architecture and platform teams to scale solutions.

Design, develop, test, deploy, and support scalable full-stack applications using Java, Spring Boot, React, microservices, REST, gRPC, messaging, and relational databases. Own initiatives from requirements through production, contribute to architecture and technical decisions, build automated tests using TDD, improve CI/CD and engineering productivity with AI-assisted tools, troubleshoot production issues, conduct code reviews, and mentor engineers while collaborating across distributed teams.

Manages and coaches multiple software engineering teams developing cloud-native B2B payment platforms, microservices, and web applications. Responsibilities include talent management, technical leadership, architecture, code quality, security, vulnerability management, testing, performance optimization, platform capacity, CI/CD automation, release workflows, incident mitigation, and engineering productivity. The role partners with product and business stakeholders, manages budgets, addresses technical debt, and ensures reliable, scalable, compliant software delivery.

Senior Software Engineer responsible for designing, developing and delivering high-quality software solutions within an agile scrum team. Collaborate with product and architects, produce design documents and proofs of concept, perform cross-team code reviews, and contribute to cloud-native platform development.

Owns service management and production readiness for mission-critical payment, data, and platform services. Leads incident and problem management, root cause analysis, change and release governance, certificate lifecycle management, risk and compliance controls, service monitoring, and continual improvement. Partners with engineering, product, operations, customer support, risk, and external stakeholders to improve resilience, reliability, customer experience, and operational outcomes across distributed environments.

Lead the modernization of Mastercard’s dispute management platform. Own the technical product roadmap and backlog, translate system designs into features and user stories, define acceptance criteria, analyze software requirements, and guide Agile delivery. Partner with Engineering and global stakeholders to prioritize work, manage dependencies, measure outcomes, improve processes, and deliver API-driven platform capabilities from design through customer integration.

Manage and mentor a cross-functional engineering team to design, build, and deploy analytics and AI-driven full-stack solutions. Lead technical direction, architect scalable data pipelines and APIs, collaborate with product and design, and champion cloud-native, testable, production-grade applications while promoting continuous improvement and responsible AI practices.