TCJ2405

techcarrot FZ; Hyderabad, Dadri, Chennai District; On-site; INR 2,500,000 - 4,200,000; Full time

Job summary

tech carrot, a leading global IT service provider, seeks an AI Engineer to design enterprise-grade GenAI systems, multi-agent and tool-augmented solutions for complex enterprise needs.

You will architect and deliver secure, scalable GenAI pipelines, integrate with Azure ecosystems, and implement RAG, hybrid search, and agent workflows across data sources, ensuring governance and production readiness.

Qualifications

• 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.
• 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

Responsibilities

• 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
• Development of scalable, secure backend and integration with enterprise systems
• Collaboration with Cloud, Digital, Data Engineering and Business teams to drive adoption

Skills

LLMs & Transformers

GenAI systems

Multi-agent design

RAG pipelines

LangChain

LangGraph

Haystack

PyTorch

TensorFlow

Azure OpenAI

Tools

Azure App Services

Azure Functions

Bot Framework

Azure Cache for Redis

Azure Data Factory

Neo4j

Databricks Vector DB

Azure AI Search

PyTorch

TensorFlow

OpenAI APIs

Job description

tech carrot is a leading global ITservice provider and partner in digital transformation offering cost-effective,customer-centric, and cutting-edge digital solutions to clients worldwide.

founded in 2016, tech carrot isheadquartered in Dubai, UAE. Being a people-oriented organization with aphilosophy of "We care" as our core DNA, tech carrot continuallyfocuses on new initiatives and strategies to increase overall employeeexperience by providing a plethora of platforms to drive employee development,overall efficiency, increase overall employee satisfaction. With over 200+technology specialists who are engaged and motivated we are growing at 20% a year-on-year since inception.

We offer cutting-edge services across multipleindustries and deliver seamless customer experiences, ensuring high value andrapid growth for our clients. tech carrot has earned wide recognition as areliable partner for organizations across the globe because of its professionalapproach and strong delivery capabilities. The Middle East and Africa arehandled by UAE operations, while APAC is handled by India operations. We havealso expanded in the USA and the Netherlands as well.

Job Description

• We are seeking a highly skilled andpassionate AI Engineer to design and build enterprise-grade,production-ready conversational and Agentic AI systems that enhance howusers interact with enterprise products, services, insights, andrecommendations.
• This role goes beyond traditionalchatbots. You will architect and deliver multi-agent, tool-augmented GenAIsolutions capable of reasoning, planning, contextual retrieval, andaction execution across multiple enterprise data sources and platforms. Youwill work on secure, scalable, and governed GenAI systems , aligned withenterprise architecture and compliance standards, ensuring reliability,explainability, observability, and continuous improvement in real-worldproduction environments
• Design,develop, and deploy production-grade GenAI solutions using advanced LLMs(OpenAI APIs such as GPT- 4.1, GPT-4o, etc.
  
• Implement Retrieval-AugmentedGeneration (RAG) pipelines using structured and unstructured enterprisedata.
  
• Design hybridsearch architectures combining Vector DBs and Graph DBs (e.g., Azure AISearch, Neo4j) for semantic, contextual, and relationship-based retrieval.
  
• Build AgenticAI workflows using frameworks such as LangChain, LangGraph, and Haystack, including:
  
• Tool-calling, function execution, and system-to-system automation
  
• Memory management (short-term, long-term, and session-based)
  
• Developand integrate AI-powered chatbots and agents within the Azure ecosystem,ensuring seamless interoperability with existing platforms and services.
  
• IntegrateGenAI solutions with enterprise systems using APIs, event-drivenarchitectures, and message brokers.
  
• Buildsecure, scalable backend leveraging Azure App Services, Azure Functions,Bot Framework, Azure Cache for Redis, and related services.
  
• Workclosely with Cloud, Digital, Data Engineering, and Business teams todrive 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.
  
• 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