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Nagarro is Hiring

Job Info:
  • Company Nagarro
  • Position Senior Staff Engineer, Python & LLM
  • Location Remote, India
  • Source SmartRecruiters
  • Published March 14, 2026
  • Category Development
  • Type Full-Time
  • Experience Senior

REQUIREMENTS:

  • Total experience 7.5+ years
  • Strong hands-on expertise in LLM engineering and Python backend development.
  • Expertise in LLM Application Frameworks, Prompt Engineering with LLMs, Python, FastAP
  • Proven experience building and deploying applications using cutting‑edge LLMs (GPT‑4/5, Claude, Gemini, Mistral, LLaMA, Mixtral, DeepSeek, etc.).
  • Strong experience with RAG pipelines, embeddings, prompt engineering, and multi‑agent systems.
  • Hands-on expertise with LLM frameworks such as LangChain, LlamaIndex, Haystack, DSPy, AutoGen, CrewAI.
  • Deep knowledge of model fine‑tuning techniques such as LoRA, QLoRA, PEFT, adapters.
  • Experience deploying open‑source LLMs using vLLM, TGI, Ollama, LM Studio, Triton, etc.
  • Strong backend engineering experience with FastAPI (expert), Django or Flask, microservices, and distributed systems.
  • Experience implementing REST, GraphQL, and streaming APIs.
  • Hands-on experience with vector databases such as Pinecone, Weaviate, Milvus, Qdrant, FAISS, Chroma.
  • Knowledge of semantic search, hybrid search, embedding pipelines, and enterprise knowledge systems.
  • Strong understanding of cloud platforms (AWS, GCP, Azure), containers, and Kubernetes.
  • Experience with MLOps/LLMOps practices—CI/CD for ML workflows, monitoring, logging, tracing, and model lifecycle management.
  • Bachelor’s/Master’s in CS, AI, Data Science, or equivalent experience.
  • Excellent communication, collaboration, and problem-solving skills.

RESPONSIBILITIES:

  • Design, implement, and optimize LLM-powered applications using leading and open‑source models.
  • Develop advanced prompt engineering, system prompts, and structured output pipelines.
  • Build RAG pipelines with hybrid search, embeddings, and custom retrieval strategies.
  • Develop multi-agent systems and autonomous AI workflows.
  • Fine‑tune, adapt, and serve foundation models using LoRA/QLoRA and modern inference engines.
  • Deploy and scale LLM workloads using vLLM, TGI, Ollama, or GPU/TPU-based systems.
  • Integrate multimodal models across text, image, audio, and video.
  • Build evaluation pipelines for hallucination detection, factual accuracy, quality scoring, and alignment.
  • Implement guardrails, moderation, and safety policies for AI systems.
  • Build scalable backend systems using FastAPI, microservices, event-driven architectures, and secure API frameworks.
  • Optimize backend performance, observability, and reliability.
  • Build ingestion pipelines for document processing, chunking, preprocessing, and semantic indexing.
  • Implement semantic, vector, and hybrid search at scale.
  • Deploy AI systems on cloud platforms, manage Kubernetes inference clusters, and optimize GPU utilization.
  • Set up CI/CD, automated testing, model versioning, and production monitoring for AI workflows.
  • Develop enterprise-grade search, knowledge systems, and document intelligence platforms.
  • Ensure robustness, security, and scalability in all AI and backend systems.
  • Stay updated with the latest GenAI, LLMOps, and backend engineering innovations and share knowledge within the technical community.

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

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