Top Tech Jobs & Startup Jobs in Pune

Design, build, deploy, and optimize agentic AI solutions on Google Cloud using Google ADK and Vertex AI. Develop AI agents, machine learning models, integrations, and MLOps workflows across services such as BigQuery, Cloud Run, and Pub/Sub. Partner with stakeholders, QA, and cloud engineers to deliver production-ready solutions, implement responsible AI safeguards, monitor performance, and improve models, prompts, grounding, and agent logic.

Design, develop, deploy, and improve agentic AI solutions using Google ADK, Vertex AI, and Google Cloud. Build integrations with enterprise systems and cloud services, manage the full AI project lifecycle, implement responsible AI safeguards, and monitor production performance. Collaborate with business stakeholders, QA specialists, and cloud engineers to deliver scalable solutions. Apply MLOps, model tuning, retrieval-augmented generation, multi-agent architectures, and multiple model providers to solve ambiguous business problems and create measurable outcomes.

Leads the design and development of scalable Java backend applications using Spring Boot, microservices, and REST APIs. Provides architectural and technical leadership, mentors engineers, drives coding standards, and oversees initiatives from design through production support. Collaborates with product, architecture, QA, DevOps, and engineering teams while resolving complex technical issues and performance bottlenecks. Preferred experience includes payments or fintech, Kafka, databases, cloud platforms, Kubernetes, security, CI/CD, and mobile application backends.

Develop and maintain scalable iOS applications using Swift, SwiftUI, and UIKit. Own features from design through production release, contribute to architecture and coding standards, integrate REST APIs and SDKs, and resolve performance and stability issues. Collaborate with Product, Design, QA, and Backend teams while applying secure coding, testing, debugging, Git, CI/CD, and App Store release practices. Enterprise mobile, FinTech, payments, and Agile experience are advantageous.

Designs and develops AI and machine learning models, deploys them into scalable production applications through APIs, microservices, and cloud platforms, and trains models on large datasets. Responsibilities include NLP, computer vision, testing, debugging, optimization, and collaboration with data scientists and software engineers. Requires proficiency in programming, machine learning frameworks, cloud and data tools, and AI development techniques.

Design, build, and scale Java-based microservices and SaaS infrastructure on AWS. Lead distributed-system architecture, REST and event-driven APIs, full-stack development, automated testing, CI/CD, observability, and performance optimization. Collaborate with product, UX, and DevOps teams, author technical designs, deliver production features, and mentor engineers. The role requires ownership of high-priority initiatives and contributions to long-term platform strategy.

Supports Mastercard’s operational risk management program across shared services. Responsibilities include identifying and assessing risks, evaluating control gaps, developing remediation plans, maintaining risk registers and audit schedules, conducting incident and root-cause analysis, monitoring KRIs, coordinating audits, and preparing leadership reporting. The role also supports compliance monitoring, process and controls documentation, risk testing, and development of AI-based preventative and detective controls.

Develops production-grade data and analytics solutions, applies statistics and machine learning to business problems, and mentors data scientists. Responsibilities include feature engineering, modeling, NLP, generative AI, MLOps, cloud AI services, stakeholder engagement, analytical storytelling, and structured problem solving within the banking, financial services, and insurance domain.

Coordinates IT and cloud infrastructure projects from planning through completion. Responsibilities include managing project trackers, schedules, budgets, risks, milestones, vendors, onboarding and offboarding, stakeholder communications, leadership meetings, and process improvements. The role serves as a liaison between IT, vendors, and end users while facilitating cross-functional collaboration and ensuring timely delivery.

Designs, deploys, and drives adoption of New Relic observability solutions for strategic customers. Architects scalable monitoring for microservices, serverless, and distributed systems; integrates observability with cloud platforms, IaC, CI/CD, and platform engineering workflows; leads technical workshops; troubleshoots deployments; and creates documentation, training, and implementation best practices.

Design and evolve scalable design-system components, interaction patterns, specifications, and usage guidelines. Build AI-assisted live prototypes, partner with UI engineers on responsive and accessible implementations, and support product designers adopting the system. The role requires strong component architecture, product/UX design experience, familiarity with AI development tools and frontend technologies, and the ability to design for complex technical domains.

Lead the technical direction, architecture, training, fine-tuning, evaluation, and production deployment of LLM and agentic AI systems for cybersecurity products. Optimize inference at scale, establish engineering standards and release evaluations, make model strategy decisions, resolve complex technical trade-offs, and mentor senior engineers. The role remains hands-on while influencing cross-team product and platform investments.

Leads advanced crashworthiness and NVH simulations for automotive seating systems using LS-DYNA and OptiStruct. Ensures compliance with global safety regulations, supports simulation-driven design optimization, mentors junior analysts, collaborates with global teams, and guides suppliers in delivering robust, lightweight, cost-effective seating solutions.