Lead AI Engineer / Senior Data Scientist

Job Role – Lead AI Engineer / Senior Data Scientist
Location – NYC,NY(Hybrid)
Full Time role
Experience range – 8 to 11 years
Salary - $135k/yr base + 5% + 5% bonus

Must have skills : Data Modeling (Strong) ,Generative & Agentic AI ,Machine Learning ,Python (Expert) ,Embeddings & Vector Databases


Job Description :
We are looking for a Lead AI Engineer / Senior Data Scientist to join our AI & Tech Accelerator. In this role, you will lead the design, development, and delivery of AI solutions, leveraging Machine Learning, Generative AI, and emerging Agentic AI patterns. You will play a key role in driving high-quality engineering practices, including code reviews, solution design, and mentoring, while remaining hands-on in development.

Key Responsibilities:
In this role, you will operate at the intersection of development, technical leadership, and delivery execution.

Design & Develop AI Solutions:
Design and build scalable AI/ML solutions using Machine Learning, Deep Learning, and Large Language Models (LLMs). Contribute actively to development, ensuring high-quality, production-ready code.

Code Review & Quality Governance:
Lead code reviews and enforce best practices across the team, ensuring maintainability, scalability, and performance of AI systems. Establish coding standards and improve engineering quality.

Generative & Agentic AI Implementation:
Develop and implement Generative AI use cases, including RAG pipelines, prompt engineering, embeddings, and LLM integrations. Contribute to building agentic workflows and multi-step reasoning systems.

Solution Delivery & Business Impact:
Deliver AI solutions across business domains (marketing, supply chain, retail, operations), ensuring alignment with business requirements and measurable impact.

Technical Leadership:
Guide junior team members, support design decisions, and contribute to solution architecture under the guidance of senior architects.

Cross-functional Collaboration:
Work closely with Data Engineers, Product Managers, and DevOps teams to integrate AI models into scalable production systems.

Mentorship & Knowledge Sharing:
Mentor team members, support onboarding, and promote best practices across AI/ML development and deployment.

What We Are Looking For:
We are seeking a hands-on technical leader who can balance coding, code quality ownership, and team guidance, with a strong focus on delivery excellence.

Education & Experience:
Bachelor's or Master's degree in Computer Science, AI, Data Science, or a related field
8–9.5 years of experience in AI/ML development and delivery
Proven experience in building and deploying production-grade AI/ML solutions
Strong experience in code reviews and team-level technical leadership
Technical Expertise:

AI/ML & Advanced Analytics:
Strong expertise in Machine Learning, Deep Learning, and statistical modeling
Experience in developing and deploying ML models in production

Generative AI & LLMs:
Hands-on experience with LLMs (GPT, Claude, Llama, Gemini)
Experience in:
RAG (Retrieval-Augmented Generation)
Prompt Engineering & Context Handling
Embeddings & Vector Databases
Exposure to agentic frameworks (LangGraph, CrewAI, AutoGen) is a plus

Programming & Engineering:
Strong proficiency in Python, SQL, and software engineering principles
Experience with APIs, microservices, and scalable backend systems

MLOps & DevOps:
Experience with CI/CD pipelines, model deployment, and monitoring
Familiarity with tools like MLflow, Vertex AI, or similar platforms

Cloud & Data Platforms:
Experience with GCP (preferred) or other cloud platforms
Understanding of data pipelines, data lakes, and real-time processing
Soft Skills & Mindset:

Technical Ownership: Takes responsibility for code quality, delivery, and technical decisions within the team
Collaboration: Works effectively across teams and contributes to a strong engineering culture
Problem Solving: Ability to break down complex problems and deliver practical AI solutions
Communication: Clearly articulates technical concepts to both technical and non-technical stakeholders

Additional Expectations (Lead Level):
Own code quality, review processes, and engineering best practices
Contribute to solution design and architecture discussions
Ensure timely and high-quality delivery of AI solutions
Support adoption of best practices in AI/ML and Generative AI development