TCJ2487

techcarrot FZ; Hyderabad, Dadri, Chennai; On-site; INR 2,500,000 - 6,000,000; Full time

Job summary

tech carrot is seeking a highly skilled 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.

You will architect multi-agent, tool-augmented GenAI solutions capable of reasoning, planning, contextual retrieval, and action execution across enterprise data sources and platforms.

Qualifications

• Strong understanding of LLMs, transformers, embedding, 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 deploying GenAI solutions on Azure, including: Azure Data Factory (ADF) and Databricks.

Responsibilities

• Design and build enterprise-grade, production-ready conversational and agentic AI systems.
• Architect and deliver multi-agent, tool-augmented GenAI solutions with reasoning, planning, and action execution.
• Develop production-grade GenAI solutions using advanced LLMs including OpenAI APIs.
• Implement Retrieval-Augmented Generation (RAG) pipelines across enterprise data sources.
• Design hybrid search architectures using Vector and Graph databases for semantic retrieval.
• Build Agentic AI workflows using LangChain, LangGraph, and Haystack with tool-calling and automation.
• Develop secure backend on Azure services and integrate with existing platforms.
• Collaborate with Cloud, Digital, Data Engineering, and Business teams to drive adoption.

Skills

GenAI system design

End-to-end GenAI products

Multi-agent architectures

Reasoning & action workflows

Azure deployment

PyTorch & TensorFlow

Tools

LangChain

LangGraph

n8n

Co-pilot

Job description

Hyderabad, Noida, Chennai, India

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 is headquartered in Dubai, UAE. Being a people-oriented organization with philosophy of "We care" as our core DNA, tech carrot continually focuses on new initiatives and strategies to increase overall employee experience 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 multiple industries and deliver seamless customer experiences, ensuring high value and rapid growth for our clients. tech carrot has earned wide recognition as a reliable partner for organizations across the globe because of its professional approach and strong delivery capabilities. The Middle East and Africa are handled by UAE operations, while APAC is handled by India operations. We have also expanded in the USA and the Netherlands as well.

Office Location

Hyderabad, Chennai, Noida

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
• 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 hybridsearch 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:
• Tool-calling, function execution, and system-to-system automation
  
• Memory management (short-term, long-term, and session-based)
  
• 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.
• 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