Senior Manager, Engineering

Senior Manager, AI
Pune
About the role
The Senior Engineering Manager within the NIQ Analytics organization will report to the Director, Analytics Engineering and be responsible for leading a high-performing team of software engineers while driving the development of innovative AI-enabled product solutions for our rapidly expanding customer base. This role operates in an open, collaborative, and innovation-driven environment, leveraging modern client and server-side technologies, Generative AI, and Agentic AI to deliver scalable and impactful solutions. 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, and the productionization of AI-enabled capabilities.
Key Responsibilities:
Lead the architecture, design, and productionization of scalable microservices and AI-enabled product capabilities from concept through production deployment.
Lead AI platform system design and implementation, ensuring robust, secure, maintainable, and well-governed solutions across Java/Spring Boot and Python/FastAPI services where appropriate.
Drive the architecture and delivery of Generative AI and Agentic AI solutions, including MCP-based architectures, agent orchestration, tool integration, intent classification, agent state management, and multi-agent workflows.
Establish engineering patterns for integrating LLM APIs, including OpenAI, Azure OpenAI, Anthropic, and equivalent providers, with attention to security, reliability, cost, rate limits, and token efficiency.
Guide teams in productionizing GenAI use cases such as AI chatbots, summarization, classification, intelligent search, Q&A, and embedding-based retrieval.
Lead the design of systems that query and manage large-scale structured and unstructured data, including SQL, NoSQL, MongoDB, SingleStore, and Postgres, with appropriate data modeling and performance practices.
Establish architectural approaches for agentic AI systems, embeddings, vector search, context management, caching, latency optimization, and observability for AI enabled applications.
Leverage GitHub Copilot and AI-assisted development tools to accelerate software delivery, improve code quality, and enhance engineering productivity.
Take ownership of development, maintenance, testing strategy, design discussions, and operations of the team, including containerized API services.
Participate in all aspects of agile software development, including design, implementation, deployment, sprint planning, and continuous improvement.
Own the end-to-end lifecycle of new product features and components, partnering with product, design, data, and AI engineering stakeholders.
Ensure application performance, uptime, scale, and reliability while maintaining high standards of code quality, security, and thoughtful application design.
Work with a cross-functional team on products and features to drive growth and meaningful customer outcomes.
Develop engineering talent through coaching, technical mentorship, constructive reviews, and clear accountability for delivery outcomes.
Research, evaluate, and recommend emerging technologies, frameworks, and engineering practices that can strengthen the product and platform.
Influence product development through important technical decisions, system architecture, development practices, and long-term technology strategy.
12+ years of experience in Software development with at least 5+ years of experience in team management. Experience and knowledge of server-side technologies: Java/ Python, Spring Boot/ FastAPI, SQL, Agentic AI, and API-centric distributed systems.
Strong hands-on experience designing, building, and leading production-grade Generative AI, LLM, and Agentic AI systems.
Strong experience with LangChain, LangGraph, OpenAI LLMs, or comparable agent orchestration frameworks. Strong understanding of MCP-based AI architectures, including MCP servers, tools, resources, agent-tool interaction patterns, and multi-agent systems.
Experience integrating LLM APIs such as OpenAI, Azure OpenAI, Anthropic, Cohere, Mistral, or equivalent providers.
Working knowledge of Python 3.x and FastAPI, Flask, or Django for AI services and REST API integrations, alongside strong Java/Spring Boot expertise.
Strong experience in Angular/React and the ability to guide delivery of AI-enabled user experiences in partnership with front-end engineers.
Experience with Docker containers, Kubernetes, and cloud environments such as AWS, Azure, or GCP.
Experience with hybrid MongoDB/Postgres data models and modern DevOps or CI/CD practices.
Experience with large-scale SQL / NoSQL databases, including SingleStore, Postgres, and MongoDB; fluent with relational databases and data modeling.
Deep understanding of RESTful API design, security, scalability, performance, and operational best practices.
Strong problem-solving and analysis abilities, with the judgment to make sound architecture and delivery trade-offs.
Experience working in agile methodologies and sprint planning.
Must have a bachelor's degree in computer science or equivalent.

Employment type
Full-time

Work arrangement
No