12096 AI Solutions Engineer

PSEG • Newark, NJ

11d • Hybrid

About The Position

The AI Solutions Engineer (Full Stack) is responsible for evaluating, prototyping, designing, developing, and delivering enterprise AI solutions across a rapidly evolving technology landscape. This role combines hands-on AI engineering, full-stack application development, solution architecture, cloud integration, and technology evaluation responsibilities to accelerate enterprise AI adoption and establish scalable, secure, and reusable AI solution patterns. This role is expected to actively build and deliver AI-enabled applications and solutions. The position will partner closely with business stakeholders, enterprise technology teams, platform owners, cybersecurity, to rapidly prototype, implement, and operationalize AI capabilities across the enterprise.

Requirements

• Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field
• 6+ years of experience in software engineering, full-stack application development, cloud engineering, AI/ML technologies, or solution development
• Hands-on experience designing, developing, and integrating full-stack cloud-based applications, APIs, and enterprise solutions
• Experience prototyping, building, and delivering AI, Machine Learning, Generative AI, or intelligent automation solutions
• Experience developing web applications, APIs, workflow applications, or user-facing enterprise applications
• Strong understanding of cloud platforms, distributed systems, APIs, enterprise integration patterns, and modern application development practices
• Strong communication, problem-solving, and stakeholder engagement skills
• Compliance with the Department of Energy's regulation 10 CFR 810 is required.

Nice To Haves

• Experience with enterprise AI technologies and cloud AI services such as Azure OpenAI, AWS Bedrock, Azure AI Services, or similar platforms
• Experience building AI agents, copilots, Retrieval-Augmented Generation (RAG) solutions, orchestration workflows, chat interfaces, or GenAI-enabled applications
• Familiarity with enterprise platforms including ServiceNow, Salesforce, SAP, and AI-enabled enterprise applications
• Experience with Python, REST APIs, orchestration frameworks, vector databases, and modern AI development frameworks
• Familiarity with front-end frameworks, lightweight UI development, cloud-native application development, and API integration
• Familiarity with DevOps, CI/CD, containerization, cloud-native development, and emerging MLOps practices
• Experience within regulated industries such as utilities, energy, financial services, or healthcare
• Understanding of AI governance, cybersecurity, risk management, and responsible AI principles

Responsibilities

• Design, develop, test, and deploy enterprise AI solutions, AI agents, copilots, APIs, and intelligent workflows
• Build AI-enabled applications, reusable services, and integrations using enterprise AI platforms and cloud technologies
• Support end-to-end solution delivery from proof of concept through production deployment
• Design scalable, secure, and maintainable AI solution architectures aligned with enterprise standards
• Develop reusable AI engineering patterns, integration frameworks, and best practices
• Define integration approaches across enterprise platforms, cloud services, APIs, and data sources
• Ensure AI solutions are scalable, observable, and operationally ready
• Partner with business stakeholders and AI Business Product Managers to evaluate AI opportunities and solution approaches
• Collaborate with Enterprise Architecture, Cybersecurity, Infrastructure, and Platform teams throughout solution delivery
• Participate in discovery workshops, technical assessments, architecture reviews, and solution design
• Ensure AI solutions comply with enterprise governance, cybersecurity, privacy, and Responsible AI standards
• Incorporate security, monitoring, logging, and operational controls into AI solutions
• Support governance reviews, risk assessments, deployment automation, and AI operational readiness
• Contribute to emerging MLOps and lifecycle management practices
• Develop rapid proof-of-concepts to validate AI use cases and business value
• Evaluate emerging AI technologies and enterprise platforms to determine the best-fit solution
• Assess technical feasibility, scalability, and integration approaches for AI solutions
• Recommend AI technologies, frameworks, and architecture patterns to support enterprise adoption

Benefits

• medical
• dental
• vision
• parental leave
• family leave programs
• behavioral health programs
• 401(k) with company match
• life insurance
• tuition reimbursement
• generous paid time off

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level