NaukriGulf

About the Role

We are looking for a hands-on Agentic AI Engineer with 2–6 years of experience in software engineering, AI, Generative AI, or related fields. The candidate must have proven experience building agentic AI solutions and practical experience with at least one agentic framework such as LangGraph or CrewAI. You will design and build intelligent agents and multi-agent workflows that can reason over context, use tools, retrieve information, make decisions, and execute multi-step tasks for NaukriGulf's jobseeker and recruiter experiences.

Key Responsibilities

Design, develop, test, and deploy production-grade single-agent and multi-agent AI solutions.

Build agent workflows using LangGraph, CrewAI, or equivalent frameworks, including orchestration, routing, state, memory, planning, and human-in-the-loop controls.

Integrate LLMs with APIs, databases, search, RAG, vector stores, enterprise services, and external/internal tools.

Implement tool/function calling, structured outputs, context management, retries, fallbacks, and error handling.

Build RAG and knowledge-grounded solutions using embeddings, vector/hybrid search, retrieval and reranking.

Develop evaluation, monitoring, tracing, and testing for agent accuracy, task completion, latency, cost, reliability, and safety.

Work with engineering, product, data, and business teams to convert business problems into measurable agentic AI solutions.

Write clean, scalable, production-grade Python and follow engineering best practices including Git, testing, code reviews, CI/CD, and documentation.

Run A/B experiments and interpret results to guide product and model decisions

Experience building and working on large-scale, production-grade systems using Java or Python.

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Must-Have Skills

2–6 years of hands-on experience in software engineering, AI/ML, Generative AI, NLP, or a related field.

MANDATORY: Proven hands-on experience developing and deploying agentic AI solutions — beyond prompt engineering or basic chatbot development.

MANDATORY: Hands-on experience with at least one agentic framework such as LangGraph,CrewAI, AutoGen, Semantic Kernel, OpenAI Agents SDK, or equivalent are also relevant.

Strong Python programming and production software development skills.

Solid understanding of LLMs, prompting, tool/function calling, structured outputs, context engineering, and model selection.

Practical experience with RAG, embeddings, vector databases/search, and knowledge-grounded generation.

Experience integrating agents with REST APIs, databases, microservices, and enterprise systems.

MCP (Model Context Protocol) and reusable AI tool/server development.

Multi-agent architectures, agent memory/state management, and human-in-the-loop workflows.

Good to Have

LangSmith, Langfuse, Arize Phoenix, or similar agent observability/evaluation tools.

Experience with OpenAI, Anthropic Claude, Gemini, Llama, Qwen, Mistral, or other LLMs.

Experience working with Docker/Kubernetes.

Experience with AI security, prompt-injection protection, tool authorization, PII protection, and cost/latency optimization.

Python ML ecosystem: Scikit-learn, Pandas, NumPy, Matplotlib/Seaborn.

Understanding and practical experience across core ML domains:

Supervised learning — Classification and Regression

Unsupervised learning — Clustering and Dimensionality Reduction

Natural Language Processing (NLP) and text-based feature extraction

Recommendation Systems or Information Retrieval

📌 SSE/Lead Engineer (Noida)
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