Lead Engineer

Questhiring; Gurugram District; On-site; INR 4,200,000 - 6,500,000; Full time

Job summary

Questhiring in Gurugram seeks a Lead Agentic AI Engineer to drive design, development, and delivery of next‑generation AI-powered Agentic AI applications. The role blends strong Java and Python software engineering with hands‑on experience in LLMs, RAG, LangChain, LangGraph, AI Agents, and GenAI architectures to build scalable, enterprise AI solutions.

You will architect intelligent agents, integrate LLM capabilities into enterprise applications, and lead cross‑functional teams across backend,

Qualifications

• 8+ years of software engineering experience with Java/Python
• Hands-on Generative AI/Agentic AI experience
• Proven use of LLMs, RAG, LangChain/ LangGraph
• Strong API design and microservices experience
• Experience with vector databases and AI workflows

Responsibilities

• Design, develop, and deploy Agentic AI applications and intelligent AI agents
• Build RAG-based applications with document ingestion, embeddings, and vector search
• Develop multi-step AI workflows and autonomous agent systems
• Integrate LLMs with enterprise APIs and data sources
• Design tool-calling, memory, planning, and orchestration capabilities
• Evaluate and optimize AI performance, reliability, and security

Skills

Java

Python

LLMs

GenAI

RAG

LangChain

LangGraph

AI Agents

REST APIs

Software architecture

Multithreading

Tools

Pinecone

Weaviate

Milvus

Qdrant

FAISS

Job description

We are looking for a Lead Agentic AI Engineer to drive the design, development, and delivery of next-generation AI-powered and Agentic AI applications. The ideal candidate will combine strong software engineering expertise in Java and Python with hands-on experience in LLMs, RAG, LangChain, LangGraph, AI Agents, and modern GenAI architectures.

This role requires an engineer who can build scalable, high-performance AI applications, modernize legacy systems, and work across backend, APIs, and AI/ML engineering. You will play a key role in architecting intelligent agents and integrating LLM capabilities into enterprise applications.

Key Responsibilities

Agentic AI & GenAI Engineering

• Design, develop, and deploy Agentic AI applications and intelligent AI agents using LLMs and modern AI frameworks.
• Build RAG-based applications including document ingestion, chunking, embeddings, vector search, retrieval, reranking, and contextual generation.
• Develop multi-step AI workflows and autonomous agent systems using LangChain, LangGraph, or equivalent frameworks.
• Integrate LLMs with enterprise APIs, databases, knowledge bases, and external tools.
• Design agent tool-calling, memory, planning, orchestration, and workflow execution capabilities.
• Evaluate and optimize LLM/Agent performance, reliability, latency, and response quality.
• Apply appropriate prompt engineering, guardrails, observability, evaluation, and security practices for production AI systems.
• Stay current with emerging developments in Generative AI, Agentic AI, LLMs, RAG, and AI engineering.

Software Engineering

• Develop robust, scalable, and high-performance applications using Java, Java 8+, multithreading, concurrency, and design patterns.
• Design and implement clean, maintainable, and production-grade software components.
• Refactor and modernize legacy Python applications and codebases to improve scalability, maintainability, and performance.
• Develop Python libraries, frameworks, automation scripts, and reusable components for AI and enterprise applications.
• Participate in the development and enhancement of enterprise/risk applications using Java technologies.
• Design and integrate RESTful APIs and microservices for AI and business applications.

API & Quality Engineering

• Develop and execute API-level testing for Java and Python-based applications.
• Test RESTful web services and validate API functionality, performance, security, and reliability.
• Build automated test suites and integrate testing into CI/CD pipelines.
• Collaborate with QA and engineering teams to establish robust testing strategies for AI-enabled applications.
• Leverage tools such as Rest Assured, Selenium, and Appium where applicable.

Technical Leadership

• Lead technical design and architecture discussions for Agentic AI and enterprise applications.
• Mentor engineers and establish best practices for AI engineering, Java, Python, APIs, testing, and software architecture.
• Conduct code reviews and ensure adherence to engineering standards and design principles.
• Work closely with Product, Engineering, Data Science, and Architecture teams to translate business requirements into scalable AI solutions.
• Identify opportunities to introduce AI automation and intelligent workflows into existing enterprise applications.

Required Skills & Experience

• 8+ years of overall software engineering experience.
• Strong hands-on experience with Generative AI / Agentic AI solutions.
• Proven experience with LLMs, RAG, LangChain, LangGraph, or similar AI frameworks.
• Strong programming expertise in Python and Java.
• Strong knowledge of Java 8+, Java EE, multithreading, concurrency, and design patterns.
• Strong understanding of RAG architecture, vector databases, embeddings, retrieval pipelines, and LLM integration.
• Experience designing and consuming REST APIs and microservices.
• Strong Python scripting and ability to develop reusable Python libraries.
• Strong understanding of software architecture, scalability, performance, and clean coding principles.
• Experience with API testing and automation.

Good to Have

• Experience with LangGraph-based multi-agent systems.
• Experience with AI Agents, tool calling, function calling, memory, planning, and orchestration.
• Exposure to vector databases such as Pinecone, Weaviate, Milvus, Qdrant, or FAISS.
• Experience with OpenAI, Azure OpenAI, Anthropic, Gemini, or other foundation models.
• Experience with LLM evaluation, observability, prompt management, and AI guardrails.