Senior Staff Engineer - Generative AI and Machine Learning

Nagarro Softwares Pvt. Ltd

Bengaluru

On-site

INR 400,000 - 700,000

Full time

14 days+
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Job summary

Nagarro Softwares Pvt. Ltd in Bengaluru seeks Senior Staff Engineer for Generative AI, LangChain + LangGraph, and ML. You will design and deploy enterprise GenAI and agentic AI solutions, drive RAG architectures, and optimize prompts while collaborating with cross-functional teams to productionize AI capabilities.

The role requires 7.5–12 years in DS/ML/AI with hands-on GenAI, LangChain, LangGraph, and LangSmith experience; knowledge of vector databases and memory architectures is essential.

Qualifications

  • 7.5–12 years of experience in DS, ML and AI.
  • Strong hands-on GenAI, LLMs, and agentic AI systems.
  • Proven expertise with LangChain, LangGraph, and ecosystem tools.
  • Experience designing Retrieval Augmented Generation (RAG) solutions.
  • Prompt engineering, instruction tuning, planning loops, and self-reflection.
  • Experience with LangSmith for tracing, monitoring, and testing.
  • Knowledge of vector databases and embeddings (FAISS, PGVector, etc.).
  • Experience building intelligent agents, tool-calling, and multi-agent systems.
  • Memory architectures: episodic, semantic, long-term vector memory.
  • Experience integrating AI with APIs and enterprise knowledge sources.
  • ML concepts: feature engineering, model development, tuning, evaluation.
  • Knowledge of MLOps: monitoring, drift detection, quality management.
  • Hands-on with AWS/Azure/Databricks.

Responsibilities

  • Design, develop, and deploy enterprise GenAI and agentic AI solutions.
  • Build scalable GenAI apps using LangChain and LangGraph.
  • Design advanced RAG architectures to improve retrieval accuracy.
  • Develop and optimize prompt engineering strategies.
  • Build intelligent agents with tool calling and orchestration.
  • Develop multi-agent systems for complex workflows.
  • Implement memory-driven agent architectures for long-term knowledge.
  • Create evaluation frameworks to measure performance and reliability.
  • Establish monitoring, tracing, testing, and observability.
  • Collaborate with engineering to productionize AI solutions.

Skills

GenAI
LangChain
LangGraph
RAG
Prompt engineering
LLMs
Agentic AI
ML concepts
APIs integration

Education

Bachelor’s or Master’s in CS/IT

Tools

LangSmith
FAISS
Azure OpenAI
OpenSearch/PGVector

Job description

Senior Staff Engineer (Generative AI, Langchain + Langraph, Machine Learning)
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 a scale — across all devices and digital mediums, and our people exist everywhere in the world (18000+ experts across 36 countries, to be exact). Our work culture is dynamic and non-hierarchical. We are looking for great new colleagues. That is where you come in!

Job Description Requirements
  • 7.5 to 12 years of overall experience in Data Science, Machine Learning, and Artificial Intelligence.
  • Strong hands‑on experience with Generative AI fundamentals, Large Language Models (LLMs), and Agentic AI systems.
  • Proven expertise in developing GenAI applications using LangChain, LangGraph, and associated ecosystem tools.
  • Experience designing and implementing Retrieval Augmented Generation (RAG) solutions, including retrieval, reranking, chunking, memory management, and context optimization.
  • Strong understanding of prompt engineering techniques, including instruction tuning, ReAct frameworks, reasoning strategies, planning loops, and self‑reflection mechanisms.
  • Hands‑on experience with LLM evaluation frameworks, model assessment, and GenAI quality measurement methodologies.
  • Experience using LangSmith for tracing, monitoring, debugging, evaluation, regression testing, and performance optimization of GenAI applications.
  • Strong knowledge of Vector Databases and Embeddings, including FAISS, Azure AI Search, OpenSearch, PGVector, or similar technologies.
  • Experience building intelligent agents, tool‑calling agents, planner‑executor frameworks, multi‑agent systems, and hierarchical agent architectures.
  • Good understanding of memory architectures, including episodic memory, semantic memory, and long‑term vector‑based memory systems.
  • Experience integrating AI agents with APIs, enterprise applications, knowledge repositories, and external tools.
  • Strong foundation in classical Machine Learning concepts, including feature engineering, model development, hyperparameter tuning, and model evaluation.
  • Experience working with structured and unstructured datasets for predictive and analytical use cases.
  • Understanding of MLOps concepts, including model monitoring, data drift detection, concept drift analysis, and model quality management.
  • Hands‑on experience with cloud platforms such as AWS, Azure, or Databricks.
  • Proficiency with version control systems and collaborative development tools such as Git and GitHub.
  • Strong problem‑solving, analytical, communication, and stakeholder management skills.
  • Candidate should have an official notice period of 30 days or less and must be able to join within one month.
Responsibilities
  • Design, develop, and deploy enterprise‑grade Generative AI and Agentic AI solutions using modern LLM frameworks and tools.
  • Build scalable GenAI applications leveraging LangChain, LangGraph, and related ecosystem technologies.
  • Design and implement advanced RAG architectures to improve response quality, grounding, and knowledge retrieval accuracy.
  • Develop and optimize prompt engineering strategies to enhance reasoning, planning, tool usage, and response generation capabilities.
  • Build intelligent agents capable of tool calling, workflow orchestration, task planning, and autonomous decision‑making.
  • Develop multi‑agent systems and agent collaboration frameworks for complex business workflows.
  • Implement memory‑driven agent architectures supporting contextual awareness and long‑term knowledge retention.
  • Create evaluation frameworks to measure performance, reliability, robustness, and business effectiveness of AI solutions.
  • Establish monitoring, tracing, testing, and observability frameworks using LangSmith and related tools.
  • Build and integrate Model Context Protocol (MCP) based services and external tool integrations.
  • Enable AI systems to interact with APIs, applications, code execution environments, and enterprise knowledge sources.
  • Apply Machine Learning techniques to solve business problems involving structured and unstructured data.
  • Perform model development, feature engineering, model optimization, validation, and performance analysis.
  • Collaborate closely with engineering, architecture, and cross‑functional teams to productionize AI and ML solutions.
  • Ensure scalability, security, maintainability, and reliability of AI‑powered applications.
  • Support MLOps initiatives, including model monitoring, drift detection, performance tracking, and continuous improvement.
  • Maintain comprehensive technical documentation, coding standards, and quality assurance practices throughout the development lifecycle.
  • Stay current with emerging trends, frameworks, tools, and best practices in Generative AI, Agentic AI, Machine Learning, and AI Engineering.
Qualifications
  • Bachelor’s or master’s degree in computer science, Information Technology, or a related field.
  • Experience Level Senior Level
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