TCJ2453

techcarrot FZ; Hyderabad, Chennai District, Dadri; Vor Ort; INR 1.800.000 - 2.400.000; Vollzeit

Zusammenfassung

tech carrot is seeking an AI Engineer to design and build enterprise-grade, production-ready GenAI systems that enhance how users interact with enterprise products and services. You will craft multi-agent, tool-augmented GenAI solutions with reasoning, planning, and contextual retrieval across diverse data sources and platforms.

Join a security-conscious, scalable GenAI program leveraging Azure, LangChain, and modern ML frameworks to deliver reliable, explainable AI with governance and

Jobbeschreibung

Hyderabad, Chennai, Noida, India | Posted on 09/30/2026

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 GenAIsolutions 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 VectorDBs and Graph DBs (e.g., Azure AI Search, Neo4j) for semantic, contextual, andrelationship-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 withinthe Azure ecosystem , ensuring seamless interoperability with existingplatforms and services.
• Integrate GenAI solutions with enterprise systems using APIs,event-driven architectures, and message brokers .
• Build secure, scalable backends leveraging Azure AppServices, Azure Functions, Bot Framework, Azure Cache for Redis , andrelated services.
• Work closely with Cloud, Digital, Data Engineering, andBusiness teams to drive adoption and real-world impact.

Production Readiness, MLOps& LLMOps

• Apply MLOps / LLMOps best practices across thelifecycle:
• Model/version management andprompt versioning
• CI/CD pipelines for GenAIapplications
• Automated testing (prompt,retrieval, and regression testing)
• Monitoring, logging, andobservability for LLM outputs
• Implement guardrails for safety, hallucinationcontrol, data privacy, and responsible AI.
• Ensure enterprise-grade governance , including accesscontrol, auditability, and compliance with internal policies.

Performance Optimization& Continuous Improvement

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

Requirements

• 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 GraphDatabases (Azure AI Search, Neo4j, Databricks Vector DB) for hybrid,semantic and relationship-driven search.
  
• Proven experience implementing RAG pipelines withstructured and unstructured enterprise data.
  
• Hands-on experience with PyTorch and TensorFlow.
  
• Experience working with high-performance, large-scale MLsystems in production environments
  
• Ability to solve complex problems in languageunderstanding, reasoning, and GenAI system design
  
• Experience deploying GenAIsolutions on Azure, including:
  
• Databricks