Job Description: GenAI Engineer
| Position: |
GenAI Engineer |
| Location: |
Gurgaon |
| Experience: |
5 – 7 Years |
Role Overview
We are seeking a talented and driven GenAI Engineer with 5 – 7 years of
experience to join our dynamic team. In this role, you will leverage your
analytical skills, machine learning expertise, and Generative AI
capabilities to manage Gen AI pipelines / workflows, extract insights from
unstructured datasets, build intelligent AI solutions, and contribute to
the development of innovative, scalable systems that enhance our products
and services.
Key Responsibilities
-
Manage GenAI models production pipelines to debug defects and provide
root cause assessments.
-
Build and orchestrate LLM - based workflows using frameworks such as
LangChain, including prompt engineering and pipeline design.
-
Implement Retrieval - Augmented Generation (RAG) architectures
leveraging vector databases such as Pinecone for semantic search and
contextual retrieval.
-
Work with document ingestion and extraction workflows, including
processing unstructured documents (PDFs, scans, forms) using tools like
AWS Extract and GenAI - based extraction techniques.
-
Collaborate with cross - functional teams (engineering, product, and
business stakeholders) to define data requirements, evaluation metrics,
and success criteria.
-
Communicate findings and insights effectively to both technical and non
- technical audiences through visualizations, reports, and
presentations.
-
Stay current with industry trends, tools, and best practices in
Generative AI, LLMs, data science, and analytics.
-
Mentor junior team members and contribute to a culture of continuous
learning and technical excellence.
Qualifications
-
Bachelor’s or Master’s degree in Data Science, Computer Science, AI/ML,
Statistics, Mathematics, or a related field.
-
4 – 7 years of experience in a data science, applied ML, or GenAI role,
with a strong portfolio of projects.
-
Hands - on experience with machine learning frameworks (scikit - learn,
TensorFlow, PyTorch).
-
Practical experience with LLMs, GenAI frameworks, LangChain, and prompt
- driven workflows.
-
Strong understanding of RAG patterns, vector embeddings, and vector
databases such as Pinecone.
Preferred Skillset
- Experience with big data technologies such as Spark or Hadoop.
-
Familiarity with deploying ML and GenAI solutions on cloud platforms
(AWS).
- Palantir Experience is an added advantage.
-
Exposure to productionizing LLM pipelines, monitoring, and evaluation.
-
Domain experience in finance, insurance, healthcare, or other data -
intensive industries.
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