AI Engineer

Zohorecruit; Chennai District; On-site; INR 1,500,000 - 3,200,000; Full time

Job summary

tech carrot, Hyderabad, Chennai, Noida, India, seeks a highly skilled AI Engineer to design and build enterprise-grade GenAI systems that power conversational agents and tool-augmented workflows.

You will architect multi-agent architectures, implement RAG pipelines, integrate with Azure, and collaborate with Cloud and Data teams to deliver secure, scalable solutions.

Qualifications

• Strong understanding of LLMs, transformers, embeddings, 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.

Responsibilities

• Design, develop, and deploy production-grade GenAI solutions using advanced LLMs (OpenAI APIs such as GPT-4.1, GPT-4o).
• Build agentic AI workflows using LangChain, LangGraph, and Haystack, including tool-calling, function execution, and system-to-system automation.
• Implement Retrieval-Augmented Generation (RAG) pipelines across enterprise data.
• Design hybrid search architectures combining Vector DBs and Graph DBs for semantic and contextual retrieval.
• Develop and integrate AI-powered chatbots and agents within the Azure ecosystem.
• Integrate GenAI solutions with enterprise systems using APIs, event-driven architectures, and message brokers.
• Build secure, scalable backends leveraging Azure App Services, Azure Functions, Bot Framework, Azure Cache for Redis.
• Collaborate with Cloud, Digital, Data Engineering, and Business teams to drive adoption.

Skills

LLMs

Transformers

Embeddings

Prompt engineering

Evaluation techniques

Tools

LangChain

LangGraph

n8n

Co-pilot

PyTorch

TensorFlow

Job description

Hyderabad, Chennai, Noida, 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 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.)
• Build agenticAI workflows using frameworks such as LangChain, LangGraph, and Haystack,including:
  • Tool-calling,function execution, and system-to-system automation
  • Memorymanagement (short-term, long-term, and session-based)
• 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.
• 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 backends 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

• Apply MLOps/ LLMOps best practices across the lifecycle:
  • Model/versionmanagement and prompt versioning
  • CI/CDpipelines for GenAI applications
  • Automatedtesting (prompt, retrieval, and regression testing)
  • Monitoring,logging, and observability for LLM outputs
• Implement guardrails for safety, hallucination control, data privacy, and responsible AI.
• Ensure enterprise-gradegovernance, including access control, auditability, and compliance withinternal policies.

Performance Optimization& Continuous Improvement

• Analyzechatbot and agent performance using quantitative and qualitative metrics(accuracy, latency, adoption, task completion).
• Optimizeprompts, retrieval strategies, agent flows, and system performance based onreal usage data.
• Drivecontinuous enhancement of user experience through experimentation and feedbackloops.

Requirements

• Strongunderstanding of LLMs, transformers, embeddings, prompt engineering, andevaluation techniques .
• Experiencebuilding end-to-endGenAI/Agentic AI products , including backend services and frontendweb apps.
• Hands-onexperience with LangChain, LangGraph, n8n, Co-pilot for buildingmodular, agent-based systems.
• Practicalexperience designing multi-agent architectures and orchestratingreasoning and action workflows.
• Strongexperience with Vector Databases and Graph Databases (Azure AI Search,Neo4j, Databricks Vector DB) for hybrid, semantic and relationship-drivensearch.
• Provenexperience implementing RAG pipelines with structured and unstructuredenterprise data.
• Hands-onexperience with PyTorch and TensorFlow.
• Experienceworking with high-performance, large-scale ML systems in productionenvironments
• Ability tosolve complex problems in language understanding, reasoning, and GenAI systemdesign
• Experiencedeploying GenAI solutions on Azure, including:
  • Databricks