Associate Staff Engineer

Nagarro; Maharashtra; On-site; INR 1,200,000 - 2,400,000; Full time

Job summary

Nagarro is seeking a senior AI/LLM engineer to design and deploy AI-powered security workflows. You will build frontend dashboards with React, backend services in Python/Java, and integrate multiple LLM providers for enterprise applications.

You’ll implement robust RAG pipelines, vector stores, and prompt engineering while ensuring security and governance across cloud platforms. The role requires hands-on experience with LangChain-like frameworks, CI/CD, Docker, and cloud platforms, with a

Qualifications

• 4+ years of experience in software development, AI/ML, or applied AI.
• Hands-on experience building production-grade LLM apps.
• Proficiency in React.js for scalable frontend apps.
• Strong Python experience for AI development, automation, backend services, and API integration.
• Java backend experience, REST API development, enterprise integration.
• Experience with LLM providers (OpenAI, Anthropic, Azure OpenAI, Vertex AI).
• Prompt engineering, system prompts, structured outputs, JSON schemas, function calling, tool integration.
• Experience with LangChain/LlamaIndex/LangGraph/Haystack or equivalent.
• RAG pipelines with embeddings, chunking, retrieval tuning, grounding, vector stores.
• Knowledge of vector databases (Pgvector, Pinecone, Weaviate, Chroma, FAISS).
• LLM evaluation methods and frameworks (RAGAS, DeepEval, Promptfoo, LangSmith).
• FastAPI/Flask, async programming, Python packaging, testing frameworks.
• Frontend basics (HTML, CSS, JavaScript) and backend API development.
• Git, CI/CD, Docker, Linux basics.
• Cloud platforms (Azure, AWS, GCP).
• Security concepts, CSPM, IAM, access controls; responsible AI practices.
• Experience with SIEM (Microsoft Sentinel or Splunk) and KQL/SPL queries.
• IaC (Terraform or Bicep) for cloud-native AI deployment.
• DPDP Act and RBI IT Risk exposure handling.

Responsibilities

• Design, develop, and deploy LLM-powered features for InfraSec workflows.
• AI-driven capabilities for vulnerability summarization, log triage, remediation recommendations.
• Develop frontend apps with React.js for internal tools and dashboards.
• Build backend AI services and APIs with Python; Java where needed.
• Integrate LLM providers into enterprise applications.
• Design prompt templates, system prompts, and structured-output schemas.
• Implement end-to-end RAG pipelines with embeddings and vector stores.
• Develop AI agents and tool-calling workflows.
• Create evaluation frameworks and regression test suites for quality and cost.
• Improve prompts and AI outputs via evaluations.
• Ensure responsible AI, security controls, and access management.
• Integrate AI with vulnerability scanners, SIEM, monitoring, and tickets.
• Automate MLOps tasks using Python and shell scripting.
• Test, debug, and optimize AI apps for reliability and cost efficiency.
• Maintain docs, repos, deployment artifacts, and runbooks.

Skills

Analytical thinking

Problem-solving

Communication

Ownership of AI solutions

Learning agility

Collaboration across teams

Education

Bachelor's degree in Computer Science or related field

Master's degree (preferred)

CISSP

AWS Certified Machine Learning - Specialty

Google Professional Machine Learning Engineer

Tools

React.js

Python

Java

OpenAI / Anthropic / Azure OpenAI / Vertex AI

LangChain / LlamaIndex / LangGraph / Haystack

RAG pipelines (embeddings, retrieval, grounding)

Vector databases (Pinecone / Weaviate / Chroma / FAISS)

SQL/REST API development

HTML/CSS/JavaScript

Linux / Shell scripting

Docker

Cloud platforms (Azure / AWS / GCP)

Security awareness (DPDP, RBI IT Risk)

Job 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 (18500+ experts across 39 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!

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 (18500+ experts across 39 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!

Requirements

Job Description

• Experience: 4+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.
• 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 for 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, system prompts, structured-output schemas, and function-calling workflows.
• Implement end-to-end Retrieval-Augmented Generation (RAG) pipelines, including document chunking, embeddings, vector store integration, retrieval optimization, and response grounding.
• Develop AI agents and tool-calling workflows using frameworks such as LangChain, LlamaIndex, LangGraph, Haystack, or equivalent technologies.
• Build evaluation frameworks, golden datasets, and regression test suites to measure LLM accuracy, hallucination rates, response quality, latency, and cost.
• Continuously improve prompt engineering and AI outputs through offline and online evaluations.
• Implement responsible AI and security controls, including prompt-injection protection, PII redaction, output filtering, rate limiting, audit logging, and access management.
• Integrate AI services with vulnerability scanners, ticketing platforms, SIEM solutions, monitoring tools, and other security infrastructure to enable automated workflows.
• Automate AI/ML operations activities such as data preparation, embedding refresh, evaluation runs, health checks, and monitoring using Python and Shell scripting.
• Test, debug, and optimize AI applications to ensure reliability, scalability, performance, and cost efficiency.
• Maintain technical documentation, source code repositories, deployment artifacts, and operational procedures.
• Collaborate with security, infrastructure, engineering, DevOps, and data teams to translate business requirements into practical AI-driven solutions.
• Apply infrastructure security principles and cloud security controls while designing and deploying AI services.
• Continuously explore emerging LLM models, frameworks, prompting techniques, and evaluation methodologies to improve solution quality and security posture.

Qualifications

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