GenAI Data Scientist / Programmer

GenAI Data Scientist / Programmer

Location: Jersey City, NJ – Hybrid (3 days/week onsite)

Interview: 1st Round Virtual → Final Round Onsite

Start: ASAP

Job Summary

Seeking an experienced GenAI Data Scientist / Programmer with strong hands-on expertise in Generative AI, LLM engineering, Python development, and Model Governance/Risk Management. The ideal candidate will have a proven track record of delivering enterprise-grade GenAI solutions end-to-end, rather than primarily proof-of-concept AI projects.

The candidate should have strong backend engineering skills combined with modern LLM technologies, agentic frameworks, RAG, evaluation frameworks, and experience operating AI solutions within enterprise governance and model risk requirements.

Required Skills & Experience

• 2+ years of hands-on professional experience delivering end-to-end Generative AI / LLM solutions in enterprise environments.
• Strong Python programming expertise.
• Experience building REST APIs, FastAPI, and WebSocket-based applications.
• Hands-on experience with Large Language Models such as GPT and LLaMA.
• Experience with Agentic AI frameworks, particularly LangGraph.
• Experience with MCP (Model Context Protocol) and skills-based orchestration.
• Strong experience with LangChain and LlamaIndex.
• Experience with embedding models, including all-MiniLM-L6-v2, Nomic AI, or similar.
• Hands-on experience with RAG and RAG evaluation frameworks such as:
• RAGAS
• LangSmith
• Phoenix / Arize
• Experience with enterprise data stores including Redis and MongoDB.
• Hands-on experience with Model Governance and Model Risk Management, including:
• Model documentation
• Governance and compliance requirements
• Model monitoring
• Performance controls
• Risk management for GenAI/ML solutions
• Ability to design, develop, test, deploy, monitor, and support enterprise GenAI applications.
• Strong written and verbal communication skills with the ability to explain complex technical concepts clearly.

Preferred Skills

• Java development experience.
• Experience with distributed and big data technologies:
• Apache Spark
• Kafka
• Hadoop / Hive
• Slurm
• Neo4j
• Experience with Machine Learning, classifiers, and statistical modeling.
• Experience working with enterprise-scale data and AI platforms.
• Advanced degree or equivalent experience in Data Science, Mathematics, Statistics, Computer Science, or another quantitative discipline.

Education & Experience

• Bachelor’s degree in IS/IT, Computer Science, Data Science, Mathematics, Statistics, or a related discipline, or equivalent professional experience.
• Typically 10+ years of overall IT experience, including experience contributing to or leading complex enterprise initiatives.
• Strong technical leadership and problem-solving capabilities.
• Self-starter who can work independently while collaborating effectively with cross-functional teams.

What We Are Looking For

The strongest candidates will demonstrate a combination of hands-on GenAI engineering and enterprise Model Governance/Model Risk Management experience.

We are specifically looking for candidates who have:

• Delivered production-grade GenAI/LLM solutions, not just POCs.
• Strong Python/backend engineering depth.
• Modern LLM ecosystem expertise including LangGraph, MCP, LangChain, LlamaIndex, RAG, and evaluation frameworks.
• Experience taking AI solutions through enterprise governance, documentation, monitoring, and risk controls.
• The ability to communicate technical concepts effectively to both technical and business stakeholders.

Interview Process

Round 1: Virtual interview, camera on – 30–45 minutes

Round 2: Onsite interview – 1–2 hours