Associate Principal Engineer, Agentic AI

Company Description

👋🏼We'Re Nagarro.

We are a Digital Product Engineering company that is scaling in a big way! We build products, services, and experiences that inspire, excite, and delight. We work at scale — across all devices and digital mediums, and our people exist everywhere in the world (17500+ experts across 39 countries, to be exact). Our work culture is dynamic and non-hierarchical. We're looking for great new colleagues. That's where you come in

Job Description

Requirements:

• Total experience 10+ years.
• Should have experience to architect and design scalable, autonomous AI systems with a focus on Generative AI, agentic frameworks, and foundation models
• Should be able to lead the evaluation and integration of open-source and proprietary LLMs (e.g., GPT, Claude, LLaMA, Mistral).
• Should be able to define architectures for autonomous agents, multimodal models (text, image, audio), Retrieval-Augmented Generation (RAG) systems, and natural language to SQL pipelines.
• Should be able to collaborate with product, research, and engineering teams to align AI initiatives with business strategy.
• Should have hands-on experience with frameworks such as Hugging Face Transformers, LangChain, OpenAI API, or similar.
• Deep understanding of agent orchestration frameworks (e.g., AutoGen, CrewAI, LangGraph), LLM fine-tuning (e.g., LoRA, PEFT), RAG pipelines, and vector databases (e.g., FAISS, Pinecone).
• Should be able to design solutions leveraging cloud-native architecture (AWS, GCP, Azure), with emphasis on GPU infrastructure.
• Must have experience to develop modular, goal-driven AI systems capable of task planning, memory persistence, context tracking, and multi-agent collaboration.
• Should have experience building autonomous AI agents using frameworks such as AutoGPT, LangGraph, CrewAI, or ReAct.
• Strong understanding of task decomposition, memory management, and tool augmentation in agentic workflows.
• Should have familiarity with long-context memory techniques and multi-agent coordination strategies.
• Must have hands-on experience with agent simulations, LLM-driven planning, and dynamic tool selection.
• Should have knowledge of how to embed feedback, reasoning loops (e.g., Reflexion, Chain-of-Thought), and self-correction mechanisms into GenAI agents.
• Must have experience with human-in-the-loop (HITL) oversight and reinforcement learning for autonomous systems.
• Exhibit excellent communication, leadership, and collaboration skills.

Responsibilities:

• Understanding the client’s business use cases and technical requirements and be able to convert them into technical design which elegantly meets the requirements.
• Must be able to establish best practices for fine-tuning, prompt engineering, model compression, and inference optimization.
• Should be able to Implement robust MLOps practices for model versioning, deployment, monitoring, and governance.
• Address ethical AI concerns including bias, hallucination, and data privacy in generative applications.
• Provide technical leadership in building and deploying generative models (LLMs, diffusion models, transformers, etc.).
• Ensure the responsible deployment of autonomous agents through safety layering, feedback loops, and auditability mechanisms.
• Mapping decisions with requirements and be able to translate the same to developers.
• Identifying different solutions and being able to narrow down the best option that meets the clients’ requirements.
• Defining guidelines and benchmarks for NFR considerations during project implementation.
• Writing and reviewing design document explaining overall architecture, framework, and high-level design of the application for the developers.
• Reviewing architecture and design on various aspects like extensibility, scalability, security, design patterns, user experience, NFRs, etc., and ensure that all relevant best practices are followed.
• Developing and designing the overall solution for defined functional and non-functional requirements; and defining technologies, patterns, and frameworks to materialize it.
• Understanding and relating technology integration scenarios and applying these learnings in projects.
• Resolving issues that are raised during code/review, through exhaustive systematic analysis of the root cause, and being able to justify the decision taken.
• Carrying out POCs to make sure that suggested design/technologies meet the requirements.

Qualifications

Bachelor’s or master’s degree in computer science, Information Technology, or a related field.