AI Solution Lead

AI Solution Lead

12-18 years

Location: Montvale NJ & Iselin NJ

Team and Responsibilities

Job Title:

The AI Solution Lead will work closely with engineering teams and client stakeholders to translate cutting-edge AI capabilities into reliable production systems while ensuring governance transparency and responsible AI practices.

The ideal candidate combines technical depth research awareness and strong communication skills enabling them to represent our company confidently in front of senior client stakeholders.

Key Responsibilities

AI Solution & Design

• Design and deliver enterprise-grade AI solutions leveraging Generative AI and Large Language Models.
• Define designs for LLM-based systems agentic workflows retrieval-augmented generation (RAG) and AI copilots.
• Evaluate and select appropriate models frameworks and infrastructure for production AI systems.
• Ensure scalability reliability and performance of deployed AI solutions.

Machine Learning & Model Expertise

• Provide deep technical expertise in:
• Large Language Models (LLMs)
• Transformer architectures
• Generative AI techniques
• Model evaluation and benchmarking
• Design approaches for fine-tuning prompt engineering and model adaptation.
• Guide teams on best practices in ML pipelines experimentation and model lifecycle management.

Production Deployment & MLOps

• Lead deployment of machine learning and GenAI systems into production environments.
• Architect and implement MLOps pipelines model monitoring and continuous improvement processes.
• Ensure AI systems are secure scalable and operationally maintainable.

AI Governance & Responsible AI

• Implement frameworks for:
• AI governance
• Model explainability
• Transparency
• Risk management
• Ensure compliance with enterprise AI governance standards and regulatory expectations.
• Define policies for model validation bias mitigation and responsible deployment.

Client Engagement & Technical Leadership

• Act as a trusted technical advisor to client stakeholders.
• Clearly communicate complex AI concepts to executives architects and engineering teams.
• Represent the company with credibility in technical and strategic discussions around AI adoption.
• Work closely with client teams to translate business problems into AI-driven solutions.

Research & Innovation

• Stay current with emerging developments in:
• Generative AI
• Large language models
• AI agents and agentic architectures
• AI infrastructure and tooling
• Evaluate new research and technologies to determine their practical applicability in enterprise environments.
• Help shape the organizations AI strategy and technical direction.

Required Qualifications

• Masters degree in Data Science Machine Learning Computer Science or related field.
• Strong expertise in machine learning fundamentals and modern generative AI technologies.
• Proven experience designing and deploying AI/ML systems in production environments.
• Deep knowledge of:
• Large Language Models
• Generative AI architectures
• ML pipelines and model lifecycle management
• Experience working with AI frameworks and ecosystems used for building GenAI applications.
• Experience implementing AI governance explainability and responsible AI practices.
• Strong understanding of enterprise software architecture and distributed systems.

Preferred Qualifications

• Experience with agentic AI systems and orchestration frameworks.
• Experience building RAG-based AI systems.
• Familiarity with AI platform engineering and scalable AI infrastructure.
• Contributions to AI research open-source projects or technical publications.
• Experience working with enterprise clients in regulated industries.

Key Skills

Technical Skills

• Machine Learning & Data Science
• Large Language Models (LLMs)
• Generative AI systems
• AI agents and agentic framework
• MLOps and model lifecycle management
• AI governance and explainability

Professional Skills

• Strong analytical and problem-solving capabilities
• Excellent communication and presentation skills
• Ability to simplify complex AI concepts for diverse audiences
• Collaborative mindset and ability to work effectively within teams
• Client-facing professionalism and credibility

Work Environment

• Full-time in-office role with collaboration across engineering and client teams.
• Weekly client visits for workshops and solution design sessions.
• High collaboration with data scientists engineers architects and business stakeholders.

What Success Looks Like in This Role

• Successfully designed and deliver production-grade AI systems.
• Become a trusted AI advisor to both internal teams and client stakeholders.
• Ensure responsible and governed adoption of AI technologies.
• Help organizations translate GenAI innovation into real operational value.