AI Development Manager

This is Open Kyber. We currently have an opportunity with one of our direct clients and would like to share the details with you. Please review the information below and let me know if you are interested. If you would like to be considered, kindly share your updated resume at

Job Title:

Lead AI Engineer Generative AI & Large Language Models

Location:

Montvale,NJ & Iselin,NJ (2-days to Montvale & 2-days to Iselin, NJ) Duration:
Long-term

Note:

Lead AI Engineers with hands on designing & providing solutions with 10-15+years of IT experience required Overview We are seeking a Lead AI Engineer specializing in Generative AI and Large Language Models (LLMs) to help design, deploy, and scale AI solutions for enterprise clients. This role requires deep expertise in machine learning and data science , particularly in the design, evaluation, and operationalization of modern language models and generative AI systems .

The AI Architect 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 Lead AI Engineer & Solution Design Design and architect enterprise-grade AI solutions leveraging Generative AI and Large Language Models . Define architecture 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 organization's AI strategy and technical direction .

Required Qualifications Master's 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 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 architectures 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…