Staff Engineer

Nagarro · Mumbai, , India

  • Senior
  • Full-time
  • Posted 2026-10-30
  • Confirmed live on 1 November 2026

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Job description

Job Description
Requirements

• Experience : 5.5+years

• Experience in software development, AI/ML engineering, or applied AI, including at least 1–2 years of hands-on experience building production-grade LLM applications.

• Expert-level proficiency in React.js for developing scalable, responsive, and reusable frontend applications.

• Strong hands-on experience with Python for AI development, automation, backend services, and API integration.

• Working knowledge of Java for backend services, REST API development, and enterprise application integration.

• Practical experience with LLM providers and APIs, including OpenAI, Anthropic, Azure OpenAI, Vertex AI, or equivalent platforms.

• Hands-on experience with prompt engineering, system prompts, structured outputs, JSON schemas, function calling, and tool integration.

• Strong understanding of LLM application development, AI assistants, agentic workflows, and enterprise AI integration.

• Experience with at least one LLM orchestration framework such as LangChain, LlamaIndex, LangGraph, Haystack, or equivalent.

• Hands-on experience implementing RAG pipelines, including embeddings, document chunking, retrieval tuning, grounding, and vector database integration.

• Experience with at least one vector database or search platform, such as pgvector, Pinecone, Weaviate, Chroma, FAISS, Azure AI Search, or Vertex AI Vector Search.

• Working knowledge of LLM evaluation methodologies, including evaluation datasets, regression testing, and frameworks such as RAGAS, DeepEval, Promptfoo, or LangSmith.

• Strong understanding of AI application testing, debugging, observability, performance optimization, and cost management.

• Experience with FastAPI, Flask, asynchronous programming, Python packaging, and testing frameworks.

• Basic frontend development knowledge of HTML, CSS, and JavaScript, along with backend API development experience.

• Knowledge of Shell scripting, Linux fundamentals, Git, CI/CD pipelines, and Docker.

• Exposure to at least one cloud platform such as Microsoft Azure, AWS, or Google Cloud Platform.

• Basic understanding of Infrastructure Security concepts, including vulnerabilities, patch management, security logs, IAM, and access controls.

• Awareness of responsible AI and security practices, including prompt injection, data leakage, hallucinations, bias, and content filtering.

• Familiarity with SIEM platforms such as Microsoft Sentinel or Splunk, including the ability to write KQL or SPL queries for AI-assisted security detection and investigation.

• Basic understanding of Cloud Security Posture Management (CSPM) and cloud security controls such as Network Security Groups (NSGs), Web Application Firewalls (WAF), IAM policies, and conditional access.

• Understanding of Infrastructure as Code (IaC) tools such as Terraform or Bicep for cloud-native AI service deployment and configuration.

• Exposure to data privacy and regulatory requirements applicable in India, including the DPDP Act and RBI IT Risk Framework, particularly in handling personal and sensitive data within AI systems.

• Familiarity with vulnerability management concepts, including CVE, CVSS, EPSS scoring, CISA KEV catalogue, and patch prioritization workflows.

• Strong analytical and problem-solving skills, with the ability to debug LLM behavior across prompts, retrieval pipelines, and tool integrations.

• Ability to interpret evaluation metrics, application logs, and security telemetry to improve AI quality, reliability, and operational efficiency.

• Demonstrated ownership of AI solutions from prototype to production, including evaluation, observability, testing, and documentation.

• Strong learning agility and adaptability to evolving AI models, frameworks, tools, and development practices.

• Excellent written and verbal communication skills, with the ability to collaborate effectively across technical and business teams.

• Certifications such as CISSP, Associate of ISC², CEH, Google Professional Machine Learning Engineer, AWS Certified Machine Learning – Specialty, Microsoft Azure Administrator Associate (AZ-104), CCSP, or Google Associate Cloud Engineer are preferred.
Responsibilities

• Design, develop, and deploy LLM-powered features, AI assistants, and intelligent automation solutions to support Infrastructure Security (InfraSec) workflows.

• Build AI-driven capabilities for vulnerability summarization, log triage, remediation recommendations, security policy reviews, configuration assessments, and natural-language querying of security data.

• Develop scalable, responsive, and reusable frontend applications using React.js for AI-powered internal tools and dashboards.

• Build and maintain backend AI services and APIs using Python, with Java-based backend development wherever required.

• Integrate LLM providers such as OpenAI, Anthropic, Azure OpenAI, Vertex AI, and open-source models into enterprise applications.

• Design and optimize prompt templates,

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