Top Tech Jobs & Startup Jobs in Pune

Develop and optimize Mastercard payment applications through performance testing, Java and database tuning, bottleneck analysis, automation, and APM tooling. Design load tests, measure latency and throughput, resolve system performance issues, improve testing environments, coach junior engineers, and present results to stakeholders. Requires Java Spring Boot, PostgreSQL, Oracle, JMeter, BlazeMeter, performance analysis tools, and payments industry knowledge.

Leads the architecture and development of AI-focused quality engineering frameworks, evaluation pipelines, synthetic data tools, prompt regression suites, and self-healing automation. Establishes strategies for testing hallucinations, model drift, bias, accuracy, reliability, performance, and scalability in AI-driven enterprise products. Provides architectural direction, advises executives, mentors engineers, drives cross-functional adoption of AI testing standards, and represents the company externally.

Architect and build scalable, resilient distributed systems and event-driven microservices using Java and GoLang. Lead technical design, development, testing, performance optimization, and deployment across AWS cloud infrastructure. Collaborate with product and architecture teams, establish engineering standards, mentor engineers, participate in on-call support, and drive service roadmaps for a multi-tenant SaaS identity security platform.

Build and validate technical partner integrations and AI-driven prototypes with platforms such as AWS, Google, Snowflake, OpenAI, and Anthropic. Design scalable distributed systems, RESTful APIs, integration templates, and proof-of-concept architectures. Collaborate with product managers, technology partners, and core engineering teams to transition successful prototypes into production products. Establish integration frameworks and best practices while supporting agentic workflows, cloud infrastructure, DevOps, and AI-assisted engineering.

Owns the design, development, deployment, maintenance, and production support of critical insurance applications and platforms. Responsibilities include incident resolution, root cause analysis, system integration, performance optimization, code reviews, technical design, Agile delivery, automated testing, CI/CD, modernization, documentation, and deployment leadership. The role requires hands-on full-stack expertise with Python, React, and Java, plus strong operational ownership and collaboration across global teams.

Designs and develops AI and machine learning models, including NLP and computer vision systems. Deploys models into scalable production applications using APIs, microservices, and cloud platforms. Handles large datasets, trains and optimizes models, evaluates performance, and collaborates with data scientists and software engineers to deliver business-aligned AI solutions.

Designs and operates secure, scalable AWS infrastructure for AI/ML workloads. Builds Terraform-based cloud environments, GitLab CI/CD pipelines, Kubernetes platforms, observability with Prometheus and Grafana, intelligent alerting, and self-healing systems. Tracks DORA metrics, improves reliability and cost efficiency, supports production AI/RAG deployments, establishes governance and security standards, and mentors engineers. Requires strong AWS, Terraform, Kubernetes, monitoring, scripting, and AI/ML platform experience, with preferred exposure to modern MLOps and generative AI ecosystems.

Develop and optimize Databricks ETL/ELT pipelines using PySpark, SQL, Delta Lake, and Python. Translate client business problems into technical designs, lead project modules, manage delivery tasks, mentor team members, and collaborate with architects, analysts, and clients. Responsibilities include data governance, documentation, solution architecture, testing, deployment planning, risk mitigation, and delivery of technology solutions in a hybrid, client-facing consulting environment.

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.

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.