Associate Principal Engineer, Agentic AI at Nagarro

👋🏼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!

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.

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

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