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AI/ML Engineer For Top MNC

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Onsite

AI/ML Engineer For Top MNC

LRR Technologies

AI/ML Engineer For Top MNC

Skills

Google Cloud PlatformFlaskPythonData ScienceMicroservicesMachine LearningAIAWSNo-code AutomationsFastAPIAzure

1 month ago

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Important information


Contract type:

Permanent

Salary:

₹2,750,000 – ₹3,500,000 / year

Location:

Hyderabad, Telangana, India

Work mode:

Onsite

Published on:

23 September 2026

What they need


LRR Technologies is currently hiring talented people to work with Carrier Corporation. Carrier Corporation (NYSE: CARR) is a global provider of innovative heating, ventilating, and air conditioning (HVAC), refrigeration, fire, security, and building automation technologies boasting annual sales of over $20 billion, with 58,000 employees spread across 160+ countries. For its R&D center in Hyderabad, Carrier is looking for a talented AI Lead Engineer.

Experience Required:

8 - 15 years in AI/ML development, with 3+ years specialized in Generative AI and LLM applications.

Role Overview:

The AI Lead Engineer will design, build, and operate production-grade Generative AI solutions for complex enterprise scenarios. The role focuses on scalable LLM-powered applications, robust RAG pipelines, and multi-agent systems with MCP deployed across major cloud AI platforms.

Key Responsibilities:

Technical Leadership & Development:

  • Design and implement enterprise-grade GenAI solutions using LLMs (GPT, Claude, Llama and similar families).
  • Build and optimize production-ready RAG pipelines including chunking, embeddings, retrieval tuning, query rewriting, and prompt optimization.
  • Develop single- and multi-agent systems using LangChain, LangGraph, LlamaIndex and similar orchestration frameworks.
  • Design agentic systems with robust tool calling, memory management, and reasoning patterns.
  • Build scalable Python + FastAPI/Flask or MCP microservices for AI-powered applications, including integration with enterprise APIs.
  • Implement model evaluation frameworks using RAGAS, DeepEval, or custom metrics aligned to business KPIs.
  • Implement agent-based memory management using Mem0, LangMem or similar libraries.
  • Fine-tune and evaluate LLMs for specific domains and business use cases.
  • Deploy and manage AI solutions on Azure (Azure OpenAI, Azure AI Studio, Copilot Studio), AWS (Bedrock, SageMaker, Comprehend, Lex), and GCP (Vertex AI, Generative AI Studio).
  • Implement observability, logging, and telemetry for AI systems to ensure traceability and performance monitoring.
  • Ensure scalability, reliability, security, and cost-efficiency of production AI applications.
  • Deep understanding of RAG architectures, hybrid retrieval, and context engineering patterns.
  • Translate business requirements into robust technical designs, architectures, and implementation roadmaps.
  • Drive innovation by evaluating new LLMs, orchestration frameworks, and cloud AI capabilities (including Copilot Studio for copilots and workflow automation).

Required Skills & Experience:

Core Technical

Programming: Expert-level Python with production-quality code, testing, and performance tuning.

GenAI Frameworks: Strong hands-on experience with LangChain,

LangGraph, LlamaIndex, agentic orchestration libraries.

LLM Integration: Practical experience integrating OpenAI, Anthropic

Claude, Azure OpenAI, AWS Bedrock, and Vertex AI models via APIs/SDKs.

RAG & Search: Deep experience designing and operating RAG workflows (document ingestion, embeddings, retrieval optimization, query rewriting).

Vector Databases: Production experience with at least two of OpenSearch, Pinecone, Qdrant, Weaviate, pgvector, FAISS.

Azure: Azure OpenAI, Azure AI Studio, Copilot Studio, Azure Cognitive Search.

AWS: Bedrock, SageMaker endpoints, AWS nova, AWS Transform etc.

GCP: Vertex AI (models, endpoints), Agent space, Agent Build

Preferred Qualifications:

  • Masters degree in Computer Science, AI/ML, Data Science, or related field.
  • Experience with multi-agent systems, Agent-to-Agent (A2A) communication, and MCP-based ecosystems.
  • Familiarity with LLMOps / observability platforms such as LangSmith, Opik, Azure AI Foundry
  • Experience integrating graph databases and knowledge graphs to enhance retrieval and reasoning.

Perks and Benefits:

The position will pay quite well Rs. 27.5-35 lakh per annum is the band, and the final amount may be even higher depending on your experience and expertise.

If made an offer, you will need to join in 4 weeks.

This is a lifetime opportunity for people looking to specialize in highly coveted niche futuristic skills and to work in a top multinational company with excellent employee-first initiatives. We look forward to your application.

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