Top Tech Jobs & Startup Jobs in Chennai

Lead endpoint engineering and operations for a dual UEM environment (MECM/SCCM + Intune). Own patching, client health, vulnerability remediation, OS deployment, automation with PowerShell, incident/ITSM participation, and pilot AI-assisted reliability improvements while ensuring security and compliance.

Lead ETL and data warehouse testing efforts using SQL, Python, automation frameworks and AI-assisted tools. Validate ETL/ELT processes, perform data reconciliation and lineage analysis, develop automated test frameworks, integrate tests into CI/CD, mentor junior QA, and collaborate with engineers to resolve defects and improve data quality.

Design, build, and operate scalable cloud-native data pipelines, platforms, and production services. Implement data modeling, orchestration, CI/CD, and IaC. Develop AI/LLM agent solutions, RAG, and prompt-engineered workflows. Ensure reliability, performance optimization, monitoring, and mentor junior engineers.

Lead design, develop, and maintain full-stack, cloud-native applications and APIs. Integrate and deploy AI/ML models, manage IaC (Terraform), optimize cloud infrastructure, ensure security and CI/CD, mentor junior engineers, and support incident response and on-call duties.

Lead and manage software engineering teams while ensuring code quality and timely delivery of enterprise-grade applications, providing technical oversight and mentorship.

Design, develop, test, deploy, monitor, and maintain full-stack production software using Java, Python, APIs, services, data workflows, and cloud-native components. Build automated testing and CI/CD quality gates, apply secure and maintainable engineering practices, improve observability and operational reliability, modernize legacy systems, and collaborate across product, architecture, security, data, and operations teams. Use approved AI-assisted development tools responsibly throughout the software delivery lifecycle.

Lead design and delivery of AI-powered NLP/LLM features and full-stack provider chat/voice workflows. Own end-to-end model lifecycle: data prep, experimentation, deployment, monitoring, APIs, MLOps, and on-call support. Implement responsible AI guardrails for PHI/PII, collaborate across product, security and platform teams, improve reliability, latency, test coverage, and mentor engineers.

Lead AI/ML engineering vision and roadmap for healthcare and life sciences. Oversee multiple client engagements, design and deploy scalable production-grade AI solutions (ML, NLP, deep learning, computer vision, LLMs), ensure regulatory readiness, responsible AI practices, and drive adoption and value realization while managing executive client relationships and expanding AI adoption.