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Artificial Intelligence Engineer

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Onsite

Artificial Intelligence Engineer

Dimakh Consultants Pvt.Ltd

Artificial Intelligence Engineer

Skills

Google Cloud PlatformSQL QueriesDockerFlaskPythonMachine LearningAIAWSFastAPIAzure

1 year ago

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Important information


Contract type:

Permanent

Location:

Pimpri-Chinchwad, Maharashtra, India

Work mode:

Onsite

Published on:

3 September 2026

What they need


We are looking for a skilled and innovation-driven AI Engineer with 2 years of experience in Python and Large Language Model (LLM) integration. The candidate will be responsible for building production-grade RAG (Retrieval-Augmented Generation) systems, managing vector databases, and optimizing AI performance. You will play a key role in translating business requirements into functional AI agents and chatbot architectures.

Roles and Responsibilities

  • Design, develop, and maintain RAG-based chatbot systems and AI agents.
  • Integrate Large Language Models (OpenAI, Claude, open-source LLMs) into production applications.
  • Build and manage vector databases (Pinecone, Weaviate, Milvus, etc.) for semantic search and retrieval.
  • Develop robust document ingestion, chunking, embedding, and retrieval pipelines.
  • Optimize prompt engineering strategies and overall model performance.
  • Improve response accuracy, latency, and reliability of AI systems through continuous evaluation.
  • Deploy and monitor AI services in production environments using Docker and Cloud platforms.
  • Collaborate with product and leadership teams to translate complex business needs into technical AI solutions.
  • Maintain and iterate upon existing chatbot architectures to ensure scalability.

Eligibility & Skills Educational Qualification:

  • Bachelor's or Master's degree in Computer Science, Information Technology, or a related technical field.
  • Relevant certifications in AI/ML or Cloud Computing will be an added advantage.

Technical Skills

  • Core Skills: Strong proficiency in Python and experience with RAG architecture & pipelines.
  • AI Expertise: Deep understanding of Embeddings, chunking strategies, and Prompt Engineering.
  • System Design: Ability to design scalable RAG systems and manage cost/token optimization.
  • Backend: Experience with FastAPI or Flask for REST API development.
  • DevOps: Basic knowledge of Docker, CI/CD, and Cloud infrastructure (AWS/GCP/Azure).
  • Data: Familiarity with SQL/NoSQL databases and data preprocessing techniques.
  • Nice to Have: Experience with LangChain or LlamaIndex, fine-tuning basics, and AI security awareness.

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