Top Tech Jobs & Startup Jobs in Chennai

Lead design and development of Java/J2EE applications using Spring ecosystem. Build REST/SOAP services, ensure thread-safe concurrent code, integrate messaging (Kafka/ActiveMQ), work with RDBMS, and use CI/CD and dev tools for deployments on Tomcat/Jetty/JBoss.

Validate and QA data across UI and API sources, investigate issues, manage taxonomy mismatches, compile non-automated reports, and update/maintain dashboards (Power BI/Tableau). Collaborate with Business Strategy, Investment, and Analytics teams to resolve data and KPI anomalies.

Design, execute, and maintain manual and automated tests for Salesforce Sales Cloud and CPQ. Report defects, collaborate with developers to resolve issues, and perform sprint-level and smoke testing to ensure product quality.

Unspecified associate role to support digital modernization projects. Responsibilities are missing; likely involves following instructions, assisting teams, and performing assigned tasks to support client digital experiences.

Develop and maintain Python-based solutions for generative AI and NLP tasks, including LLM fine-tuning, prompt engineering, embeddings, vector DBs, REST APIs, Docker, and cloud deployments using PyTorch/TensorFlow/JAX and frameworks like Hugging Face, LangChain, or OpenAI.

Design and execute manual and automated tests for Salesforce Sales Cloud and CPQ, report defects, collaborate with developers, and perform sprint and smoke testing.

Provide functional Oracle Fusion HCM implementation and production support. Configure approval rules, DFFs/EFFs, perform solution design, data conversions and integrations, troubleshooting, reporting, and client-facing work.

Senior Software Engineer responsible for ETL and database testing using ICDEQ. Design and execute test cases, validate data pipelines, log defects, and collaborate with development teams. Familiarity with Java or Python is a plus.

Gather and document business requirements for finance-related data projects; analyze disparate data sources; produce functional specifications and data models; validate implementations; support production deployments; investigate data quality and data lineage; collaborate with technology leads to close data completeness and accuracy gaps.

Design, fine-tune, and deploy generative AI models (LLMs, diffusion, VAEs). Build data pipelines and APIs, integrate AI into production, optimize model performance and latency, and collaborate with cross-functional teams to deliver AI-powered solutions.