Top Tech Jobs & Startup Jobs in Chennai

Lead software development for complex, scalable products using Python, AI/LLM tools, RAG pipelines, AWS, and Microsoft SQL Server. Responsibilities include designing, enhancing, and troubleshooting software; resolving customer issues; contributing to planning and estimation; developing reusable components; sharing technical knowledge; mentoring colleagues; and collaborating across teams while applying Agile, Scrum, and security engineering practices.

Develop, maintain, and enhance software solutions in cross-functional teams. Diagnose and resolve complex technical issues, support customer-reported problems, contribute to application design and reusable components, assist with planning and estimation, and mentor colleagues. Build AI-enabled applications using Python, LLM APIs, RAG pipelines, agentic orchestration, and structured extraction. Work with Microsoft SQL Server, AWS cloud services, security engineering principles, and modern software development practices.

Develop, design, and maintain backend services within a squad. Translate requirements into code, perform unit testing, troubleshoot and optimize performance, participate in code reviews, and support cloud-native deployments using containerization, orchestration, CI/CD, and distributed system patterns.

Own the strategy, roadmap, development lifecycle, and go-to-market activities for fraud analytics products. Lead customer discovery, prioritize product improvements, analyze complex data, collaborate with development and data science teams, and use market and customer insights to improve user outcomes. The role requires fraud prevention expertise, statistical modeling and AI/machine learning knowledge, strong stakeholder communication, and flexible UK-US working hours.

Leads global Analytical Editorial Operations across a 150-person organization, setting strategy, operating models, budgets, quality standards, and performance measures. Drives GenAI-enabled content transformation, including Agentic Content Platform adoption and automated updating, while improving content currency, retrieval quality, customer outcomes, and operational efficiency. Partners with Product, Technology, Data Science, commercial, and editorial stakeholders; manages authors, vendors, workforce development, organizational change, and financial performance.

Drive full-cycle sales for complex, high-value AI research workspace opportunities. Originate and close new business, support strategic renewals, expand stakeholder relationships, lead value-based workshops, and translate AI and research analytics capabilities into measurable customer outcomes. Engage senior decision-makers across enterprise, government, academic, and research organizations while developing pipelines, territories, business cases, negotiations, and long-term account growth.