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AI Engineer

Talentmate

India

10th November 2026

2611-3767-76

Job Description

We are seeking a highly skilled and passionate AI Engineer to design and build enterprise-grade, production-ready conversational and Agentic AI systems that enhance how users interact with enterprise products, services, insights, and recommendations.
This role goes beyond traditional chatbots. You will architect and deliver multi-agent, tool-augmented GenAI solutions capable of reasoning, planning, contextual retrieval, and action execution across multiple enterprise data sources and platforms. You will work on secure, scalable, and governed GenAI systems, aligned with enterprise architecture and compliance standards, ensuring reliability, explainability, observability, and continuous improvement in real-world production environments

GenAI & Agentic System Development

Design, develop, and deploy production-grade GenAI solutions using advanced LLMs (OpenAI APIs such as GPT- 4.1, GPT-4o, etc.

Implement Retrieval-Augmented Generation (RAG) pipelines using structured and unstructured enterprise data.

Design hybrid search architectures combining Vector DBs and Graph DBs (e.g., Azure AI Search, Neo4j) for semantic, contextual, and relationship-based retrieval.

Build Agentic AI workflows using frameworks such as LangChain, LangGraph, and Haystack, including:

Multi-agent orchestration (planner, retriever, evaluator, executor agents)
Tool-calling, function execution, and system-to-system automation
Memory management (short-term, long-term, and session-based)

Enterprise Integration & Cloud Engineering

Develop and integrate AI-powered chatbots and agents within the Azure ecosystem, ensuring seamless interoperability with existing platforms and services.

Integrate GenAI solutions with enterprise systems using APIs, event-driven architectures, and message brokers.

Build secure, scalable backend leveraging Azure App Services, Azure Functions, Bot Framework, Azure Cache for Redis, and related services.

Work closely with Cloud, Digital, Data Engineering, and Business teams to drive adoption and real-world impact.

Production Readiness, MLOps & LLMOps

Implement guardrails for safety, hallucination control, data privacy, and responsible AI

Ensure enterprise-grade governance, including access control, auditability, and compliance with internal policies

Apply MLOps / LLMOps best practices across the lifecycle:

Model/version management and prompt versioning
CI/CD pipelines for GenAI applications
Automated testing (prompt, retrieval, and regression testing)
Monitoring, logging, and observability for LLM outputs

Performance Optimization & Continuous Improvement

Analyze chatbot and agent performance using quantitative and qualitative metrics (accuracy, latency, adoption, task completion).
Optimize prompts, retrieval strategies, agent flows, and system performance based on real usage data.
Drive continuous enhancement of user experience through experimentation and feedback loops.

Requirements

Strong understanding of LLMs, transformers, embedding, prompt engineering, and evaluation techniques.

Experience building end-to-end GenAI/Agentic AI products, including backend services and frontend web apps.

Hands-on experience with LangChain, LangGraph, n8n, Co-pilot for building modular, agent-based systems.

Practical experience designing multi-agent architectures and orchestrating reasoning and action workflows.

Strong experience with Vector Databases and Graph Databases (Azure AI Search, Neo4j, Databricks Vector DB) for hybrid, semantic and relationship-driven search.

Proven experience implementing RAG pipelines with structured and unstructured enterprise data.

Proficiency in Python, SQL, Spark, and familiarity with additional languages (e.g., JavaScript).

Hands-on experience with PyTorch and TensorFlow.

Experience working with high-performance, large-scale ML systems in production environments

Ability to solve complex problems in language understanding, reasoning, and GenAI system design

Experience deploying GenAI solutions on Azure, including:Azure Data Factory (ADF)

Databricks
Azure AI Search
Databricks Genie
AI Document Intelligence
App Services, Azure Functions, Bot Framework
Azure Cache for Redis

Job Details

Role Level:	Mid-Level	Work Type:	Full-Time
Country:	India	City:	Greater Chennai Area
Company Website:	https://techcarrot.ae/	Job Function:	Data Science & AI
Company Industry/ Sector:	Other

What We Offer

About the Company

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