AI Engineer

Techcarrot; Chennai; On-site; INR 1,500,000 - 2,100,000; Full time

Job summary

Techcarrot is seeking an AI Engineer to design and build enterprise-grade, production-ready GenAI systems that augment enterprise products and workflows. You will architect multi-agent, tool-augmented solutions with reasoning, planning, and contextual retrieval across diverse data sources.

You will implement retrieval-augmented generation pipelines, hybrid search using Vector and Graph DBs, and Agentic AI workflows with LangChain, LangGraph, and Haystack, ensuring security, governance, and

Qualifications

• Strong understanding of LLMs, transformers, embedding, and evaluation techniques.
• Experience building GenAI products, including backend services and frontend apps.
• Hands-on experience with LangChain, LangGraph, n8n, Co-pilot for modular agent-based systems.
• Experience designing multi-agent architectures and orchestrating reasoning and action workflows.
• Experience with vector and graph databases for hybrid search.
• Experience deploying GenAI solutions on Azure.

Responsibilities

• Design and build enterprise-grade, production-ready conversational and Agentic AI systems.
• Architect multi-agent, tool-augmented GenAI solutions with reasoning, planning, retrieval and action execution.
• Develop production-grade GenAI using OpenAI APIs and Azure ecosystem.
• Implement RAG pipelines and hybrid search architectures for secure data access.
• Build Agentic AI workflows with LangChain, LangGraph, and Haystack.
• Collaborate with Cloud, Digital, Data, and Business teams to drive real-world impact.
• Ensure governance, security, reliability, and observability in production environments.

Skills

LLMs

Prompt engineering

GenAI

Reasoning

Multi-agent

Observability

Performance tuning

Tools

LangChain

LangGraph

Haystack

Azure

Neo4j

Databricks Vector DB

PyTorch

TensorFlow

Job description

Hyderabad, Noida, Chennai, India | Posted on 10/16/2026

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.

Office Location

Hyderabad, Chennai, Noida

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