NeerInfo Solutions
We are seeking a
Data Scientist / Generative AI Lead Consultant
with strong expertise in
Generative AI, Agentic AI, Machine Learning, and Python . In this role, you will drive end-to-end implementation of AI solutions—from problem identification to model deployment—leveraging the latest advancements in Large Language Models (LLMs), Retrieval Augmented Generation (RAG), agent frameworks, and cloud platforms. You will work closely with client stakeholders, architects, and offshore teams to build scalable, production‑grade AI systems aligned with enterprise data strategies. Responsibilities
Lead end‑to‑end development of
Generative AI and Agentic AI solutions , including business problem discovery, solution design, model development, optimization, and deployment. Fine‑tune, evaluate, and deploy
Large Language Models
and build
Advanced RAG pipelines . Architect and implement AI workflows using
LangGraph, AutoGen, Crew AI , or similar agent frameworks. Build scalable AI applications using
Python , modern ML frameworks, and cloud‑based GenAI services. Deploy solutions using platforms such as
AWS Bedrock ,
Azure OpenAI ,
Google Vertex AI , or
IBM Watson . Ingest and process
unstructured data
including PDFs, HTML, images, and audio‑to‑text pipelines. Work with
vector databases
such as FAISS, Pinecone, Weaviate, or Azure AI Search. Ensure data quality, data governance, and adherence to coding best practices across the AI lifecycle. Collaborate with agile teams, drive sprint execution, provide mentorship, and coordinate with offshore delivery teams. Build and publish reusable assets, best practices, and accelerators for AI implementations. Required Qualifications
Bachelor’s Degree or foreign equivalent (or 3 years of relevant progressive experience per year of missing education). 7+ years
of experience in Information Technology. 4+ years
of hands‑on experience in
Generative AI / Agentic AI / Machine Learning / Data Science . Strong proficiency in
Python
programming. Experience deploying AI applications using
agent frameworks
such as LangGraph, AutoGen, or Crew AI. Experience with cloud‑native GenAI services on
AWS, Azure, GCP, or IBM Watson . Hands‑on experience with
RAG , multiple LLMs, and GenAI pipelines. Experience processing unstructured data (PDF, image, HTML, OCR, audio‑to‑text). Strong understanding of data gathering, data quality, system architecture, and ML coding best practices. Experience with
vector databases
(FAISS, Pinecone, Weaviate, Azure AI Search). Experience with
Agile/Lean
development methodologies. Preferred Qualifications
Experience with multiple programming languages— Python, R, Scala, Java, SQL . Hands‑on experience with
CI/CD pipelines & DevOps
tools (Jenkins, GitHub Actions, Terraform). Proficiency with both
SQL and NoSQL databases
(PostgreSQL, MongoDB, CosmosDB, DynamoDB). Deep Learning experience:
CNNs, RNNs, LSTMs , and exposure to emerging research. Experience with AI/ML frameworks such as
TensorFlow, PyTorch, LangChain . Strong background in
LLM fine‑tuning , optimization, quantization, and local deployment. Experience building
RESTful APIs
using FastAPI, Flask, or Django. Knowledge of model evaluation tools such as
DeepEval, FMEval, RAGAS, Bedrock evaluations . Experience with
computer vision, time‑series , and NLP pipelines. Exposure to data visualization tools (Tableau) and data query tools (SQL, Hive). Strong applied statistics background (distributions, statistical testing, regression, etc.). Seniority Level
Mid‑Senior level Employment Type
Full‑time Job Function
Information Technology Benefits
Medical insurance Vision insurance 401(k) Pension plan Paid paternity leave Disability insurance
#J-18808-Ljbffr
Data Scientist / Generative AI Lead Consultant
with strong expertise in
Generative AI, Agentic AI, Machine Learning, and Python . In this role, you will drive end-to-end implementation of AI solutions—from problem identification to model deployment—leveraging the latest advancements in Large Language Models (LLMs), Retrieval Augmented Generation (RAG), agent frameworks, and cloud platforms. You will work closely with client stakeholders, architects, and offshore teams to build scalable, production‑grade AI systems aligned with enterprise data strategies. Responsibilities
Lead end‑to‑end development of
Generative AI and Agentic AI solutions , including business problem discovery, solution design, model development, optimization, and deployment. Fine‑tune, evaluate, and deploy
Large Language Models
and build
Advanced RAG pipelines . Architect and implement AI workflows using
LangGraph, AutoGen, Crew AI , or similar agent frameworks. Build scalable AI applications using
Python , modern ML frameworks, and cloud‑based GenAI services. Deploy solutions using platforms such as
AWS Bedrock ,
Azure OpenAI ,
Google Vertex AI , or
IBM Watson . Ingest and process
unstructured data
including PDFs, HTML, images, and audio‑to‑text pipelines. Work with
vector databases
such as FAISS, Pinecone, Weaviate, or Azure AI Search. Ensure data quality, data governance, and adherence to coding best practices across the AI lifecycle. Collaborate with agile teams, drive sprint execution, provide mentorship, and coordinate with offshore delivery teams. Build and publish reusable assets, best practices, and accelerators for AI implementations. Required Qualifications
Bachelor’s Degree or foreign equivalent (or 3 years of relevant progressive experience per year of missing education). 7+ years
of experience in Information Technology. 4+ years
of hands‑on experience in
Generative AI / Agentic AI / Machine Learning / Data Science . Strong proficiency in
Python
programming. Experience deploying AI applications using
agent frameworks
such as LangGraph, AutoGen, or Crew AI. Experience with cloud‑native GenAI services on
AWS, Azure, GCP, or IBM Watson . Hands‑on experience with
RAG , multiple LLMs, and GenAI pipelines. Experience processing unstructured data (PDF, image, HTML, OCR, audio‑to‑text). Strong understanding of data gathering, data quality, system architecture, and ML coding best practices. Experience with
vector databases
(FAISS, Pinecone, Weaviate, Azure AI Search). Experience with
Agile/Lean
development methodologies. Preferred Qualifications
Experience with multiple programming languages— Python, R, Scala, Java, SQL . Hands‑on experience with
CI/CD pipelines & DevOps
tools (Jenkins, GitHub Actions, Terraform). Proficiency with both
SQL and NoSQL databases
(PostgreSQL, MongoDB, CosmosDB, DynamoDB). Deep Learning experience:
CNNs, RNNs, LSTMs , and exposure to emerging research. Experience with AI/ML frameworks such as
TensorFlow, PyTorch, LangChain . Strong background in
LLM fine‑tuning , optimization, quantization, and local deployment. Experience building
RESTful APIs
using FastAPI, Flask, or Django. Knowledge of model evaluation tools such as
DeepEval, FMEval, RAGAS, Bedrock evaluations . Experience with
computer vision, time‑series , and NLP pipelines. Exposure to data visualization tools (Tableau) and data query tools (SQL, Hive). Strong applied statistics background (distributions, statistical testing, regression, etc.). Seniority Level
Mid‑Senior level Employment Type
Full‑time Job Function
Information Technology Benefits
Medical insurance Vision insurance 401(k) Pension plan Paid paternity leave Disability insurance
#J-18808-Ljbffr