GenAI Engineer

Position Details

- Role: GenAI Engineer
- Experience: 5+ Years
- Location: Gurgaon, Pune, Noida Employment Type: Full-Time
- Salary Hike: Up to 15–25% on Current Fixed CTC
- Notice Period: Immediate Joiners or Candidates Serving Notice (Joining within 30 Days)

About the Role We are looking for a highly skilled GenAI Engineer with strong hands-on experience in designing, developing, and deploying Generative AI solutions. The ideal candidate should have demonstrated end-to-end experience in building production-ready GenAI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), vector databases, and modern AI frameworks.

Preference will be given to candidates who have successfully delivered impactful GenAI implementations and are currently working with well-known product or consulting organizations.

Key Responsibilities

- Design, develop, and deploy enterprise-grade Generative AI applications.
- Build and optimize LLM-powered solutions using prompt engineering and orchestration frameworks.
- Develop Retrieval-Augmented Generation (RAG) pipelines for intelligent document search and question-answering systems.
- Implement vector embeddings and integrate vector databases such as Pinecone for semantic search.
- Fine-tune prompts and optimize model performance for business use cases.
- Build scalable machine learning and GenAI pipelines for production environments.




- Collaborate with business stakeholders, data scientists, and engineering teams to deliver AI-driven solutions.
- Monitor, evaluate, and improve LLM performance, accuracy, and reliability.
- Deploy AI/ML solutions on AWS cloud infrastructure following industry best practices.
- Contribute to architecture discussions and recommend cutting-edge AI solutions for enterprise challenges.

Mandatory Skills

- 5+ years of experience in Data Science, Applied Machine Learning, or Generative AI.
- Strong hands-on experience with end-to-end Generative AI projects.
- Expertise in Large Language Models (LLMs) and modern GenAI architectures.
- Hands-on experience with:

- LangChain

- Prompt Engineering
- Retrieval-Augmented Generation (RAG)

- Vector Embeddings
- Pinecone or other Vector Databases
- Strong programming skills in Python.
- Experience with Machine Learning frameworks:
- Scikit-learn

- TensorFlow

- PyTorch
- Strong understanding of AI/ML lifecycle and model deployment.

Preferred Skills

- Experience with Spark and/or Hadoop.
- Experience deploying ML and GenAI solutions on AWS.
- Exposure to productionizing LLM pipelines, monitoring, evaluation, and optimization.
- Experience with Palantir is an added advantage.
- Familiarity with MLOps and LLMOps practices.
- Domain experience in Finance, Banking, Insurance, Healthcare, or other data-intensive industries

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