Top Tech Jobs & Startup Jobs in Chennai

Build and maintain high-performance React and TypeScript applications for a cloud-native digital banking platform. Responsibilities include frontend architecture, state management, API integration, design systems, accessibility, security, testing, performance optimization, CI/CD integration, and GenAI-enabled development. The role partners with product, UX, backend, QA, and SRE teams, contributes to Scrum execution, and mentors engineers while owning work across the software development lifecycle.

Build and operate scalable MLOps infrastructure for machine learning development, training, inference, and monitoring. Responsibilities include Kubernetes orchestration, AWS resource management, GPU optimization, prediction and inference platforms, ML workflows, CI/CD pipelines, observability, security compliance, and LLM serving clusters. The role collaborates with ML engineers and supports reliable, high-performance AI services and production operations.

Facilitate high-stakes discussions and negotiations between Japanese- and English-speaking executives. Provide simultaneous and consecutive interpretation, translate and localize business documents, advise on cross-cultural communication and Japanese business practices, and prepare bilingual meeting documentation. Maintain terminology glossaries and support continuity across partnership discussions and project phases.

Build and operate the infrastructure, frameworks, SDKs, runtime systems, and tooling for an AI agent platform supporting ERP product teams. Develop frontend and backend systems, APIs, microservices, distributed services, cloud infrastructure, and production LLM integrations. Translate product requirements into technical solutions, ensure reliability and developer experience, contribute to architecture decisions, and mentor engineers.

Leads end-to-end development and operations for large-scale products using Go, cloud-native infrastructure, microservices, and AI-enabled delivery. Builds AI agents, makes architecture and technology decisions, drives rapid prototyping, manages releases, improves system performance and scalability, and establishes automated testing and quality processes. Leads and mentors engineers while coordinating cross-functional stakeholders and measuring business impact through delivery speed, reliability, customer value, and operational efficiency.

Lead and transform a 50-person global QA organization by developing traditional and AI testing strategies, directing performance, scalability, security, and resilience testing, allocating resources, building quality ownership, and mentoring engineers in automation, non-functional testing, and AI validation.

Ensures the quality, reliability, and performance of AI products, model outputs, datasets, and supporting data pipelines. Responsibilities include designing AI/ML test strategies, evaluating prompts and LLM responses, detecting hallucinations and bias, validating ETL/ELT processes and dataset integrity, defining model quality metrics, automating API and data validation tests, integrating tests into CI/CD, and collaborating with engineering, data science, product, and QA teams.