Data Science GenAI Engineer
Gurugram, Haryana, India
- Pay
- Pay not listed
- Work setting
Hybrid — work setting source
Work setup in the employer’s posting: Hybrid
From the employer’s posting- Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting
What you’ll work on
Full postingDesign, develop, and deploy generative AI applications using LLMs
Build and optimize prompt engineering, RAG, and fine-tuning pipelines
Integrate GenAI models into production systems via APIs, microservices, and cloud
Evaluate model performance, reduce hallucinations, and improve accuracy and latency
Implement monitoring, logging, and feedback loops for model improvement
From the employer’s posting
Design, develop, and deploy Generative AI applications using LLMs
Build and optimize prompt engineering, RAG (Retrieval-Augmented Generation), and fine-tuning pipelines.
Integrate GenAI models into production systems using APIs, microservices, and cloud platforms.
Evaluate model performance, mitigate hallucinations, and improve accuracy, safety, and latency.
Implement monitoring, logging, and feedback loops for continuous model improvement.
Tools in this posting
- JavaScript
- Python
- TypeScript
- AWS
- Azure
- GCP
- FastAPI
Source — Tool mentions in context
- 2+ years of hands-on experience in Generative AI, LLMs, or applied NLP. - Strong programming skills in Python (required); experience with JavaScript/TypeScript is a plus. - Practical experience with:
- Vector databases (e.g., Pinecone, FAISS, Weaviate, Chroma) - Experience deploying ML/AI solutions in cloud environments (AWS, Azure, or GCP). - Solid understanding of data structures, APIs, and system design.
- Ensure compliance with security, privacy, and responsible AI guidelines. - Experience in RAG based applications using LangGraph and FastAPI. - Familiarity with MLOps practices (CI/CD for ML, model versioning, monitoring).
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Oct 12, 2026 · 16 days ago
- Recorded sightings
- 126
- Last seen by us
- Oct 29, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Your next step
- Have your resume and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the pay range before committing time to the process.
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Job description
- 4–6 years of overall software engineering or ML experience.
- 2+ years of hands-on experience in Generative AI, LLMs, or applied NLP.
- Strong programming skills in Python (required); experience with JavaScript/TypeScript is a plus.
- Practical experience with:
- LLM APIs and frameworks (e.g., OpenAI-compatible APIs, LangChain, LlamaIndex)
- Prompt engineering and RAG architectures
- Vector databases (e.g., Pinecone, FAISS, Weaviate, Chroma)
- Experience deploying ML/AI solutions in cloud environments (AWS, Azure, or GCP).
- Solid understanding of data structures, APIs, and system design.
- Ability to write clean, maintainable, and testable code.
- Design, develop, and deploy Generative AI applications using LLMs (e.g., GPT-based, open-source models).
- Build and optimize prompt engineering, RAG (Retrieval-Augmented Generation), and fine-tuning pipelines.
- Integrate GenAI models into production systems using APIs, microservices, and cloud platforms.
- Collaborate with product managers, data scientists, and backend engineers to translate business needs into AI-driven solutions.
- Evaluate model performance, mitigate hallucinations, and improve accuracy, safety, and latency.
- Implement monitoring, logging, and feedback loops for continuous model improvement.
- Stay current with emerging GenAI frameworks, tools, and best practices.
- Ensure compliance with security, privacy, and responsible AI guidelines.
- Experience in RAG based applications using LangGraph and FastAPI.
- Familiarity with MLOps practices (CI/CD for ML, model versioning, monitoring).
- Knowledge of NLP concepts such as embeddings, transformers, and tokenization.
Source details
Source notes
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- Pay
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- Location & working pattern
Gurugram, Haryana, India
Working pattern and location restrictions need checking in the full posting.
- Work authorization
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