Dimakh Consultants Pvt.Ltd
Artificial Intelligence Engineer
Skills
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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