Manager, Engineering

Manager, Engineering (Full stack + AI) Chennai/Pune   About the Job The Engineering Manager within NIQ Analytics will report to the Director, Analytics Engineering and lead a high-performing team of software engineers in delivering scalable, AI-enabled product solutions. The role combines strong engineering leadership with hands on technical direction across Java, Spring Boot, Angular, Generative AI, and Agentic AI, driving modern architecture, engineering excellence, and successful delivery of innovative solutions for NIQ’s growing customer base. This is a hands-on leadership role requiring a balanced allocation of responsibilities, with approximately 50% focused on engineering leadership activities such as technical reviews, planning, stakeholder management, talent development, and delivery oversight, and 50% dedicated to hands-on software engineering, including architecture, coding, design reviews, technical problem solving. Responsibilities Shapes best practices, coding standards, and software architecture at an organizational level Lead solutions that improve API services quality, performance, and reliability across the organization Lead solutions that improve Frontend – Angular code quality, performance, and reliability across the organization Lead the development of AI-powered solutions that enhance end-user experience, simplify workflows, and drive greater productivity. Adopt and improve efficiency gain by Adopting AI tools in SDLC Optimize computing cost, performance using the appropriate software engineering principles Work closely with PL, Arch, PMO, Interfacing teams to productionize features. Enforce DevSecOps practices - Secret, SAST, DAST Progressive coverage in unit testing. Develop engineering talent through coaching, technical mentorship, constructive reviews, and clear accountability for delivery outcomes. Lead design reviews, code reviews, and platform APIs roadmap discussions Leads without authority, influencing expertise, logical reasoning, and collaboration. Knowledge of technology standards and ability to convey key aspects to team members. Research, evaluate, and recommend emerging technologies, frameworks, and engineering practices that can strengthen the product and platform. • Excellent problem-solving skills. Uses AI to design automated reliability improvements, incident simulations, and scaling patterns. Makes technical decisions with a clear understanding of business impact, cost efficiency, and long-term sustainability. 10+ years of professional experience in Platform Engineering, building scalable frontends and API Services layer integrating with upstream and downstream Defined and evolved the technical strategy for large-scale distributed systems Balanced short-term delivery needs with long-term scalability and maintainability Should have experience in design, build, deploy, refactor enterprise grade applications Deep expertise in Angular, Java, Spring Boot, and Microservices. Good to have hands-on experience in Agentic AI development using frameworks such as LangGraph, LangChain, or Google ADK. Good to have hands-on experience building RAG-based applications and solutions. Good understanding of MCP (Model Context Protocol) and A2A (Agent2Agent) protocols Strong expertise Database (RDBMS, NoSQL, Mongo, Postgres, Snowflake) Hands on in tools for Caching, Queuing (Redis Cache preferred) Experience integrating LLM APIs such as OpenAI, Azure OpenAI, Anthropic, Cohere, Mistral, or equivalent providers. Experience in Modern cloud ecosystems with Azure/ AWS/ GCP Strong expertise in DevSecOps pipeline, quality gates, tools (code coverage, testing, sast, dast) Resolved cross-team challenges by fostering open and constructive conversations Experience working in agile methodologies and sprint planning. • Must have a bachelor's degree in computer science or equivalent.