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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # 12096 AI Solutions Engineer - **Company:** Public Service Enterprise Group Incorporated - **Location:** Newark, NJ, United States - **Experience:** Expert - **Salary:** $107,600.0 - $170,300.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Software as a Service, Cloud Computing, Cloud Engineering, Cyber Security, Information Systems, Continuous Integration, DevOps, Web Development, Distributed Systems, Design of User Interfaces, Python (Programming Language), Machine Learning, Cloud Services, Azure Machine Learning, Salesforce.Com, SAP (Applications), Software Deployment, Software Engineering, Systems Integration, Enterprise Application Integration, Data Logging, Enterprise Software Applications, IT Architecture, Generative AI, Containerization, AI Platforms, Kubernetes, Information Technology, Deployment Automation, Integration Frameworks, Machine Learning Operations, Front End Software Development, Cloud Integration, Restful APIs, Servicenow - **Published:** August 2, 2026 - **Apply:** https://dejobs.org/x/x/148AB6DFCCA24FF7B40CAC444F80E2F9/job/ ## About the Role * 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. Desired * 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 applicationsFamiliarity 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 ## Description 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. Job Responsibilities AI Solution Development & Delivery 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 AI Architecture & Engineering 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 Cross-Functional Collaboration 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 Responsible AI, Security & Operational Readiness 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 AI Prototyping & Technical Experimentation 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 ## Related Videos - [Understanding Kubernetes in a visual way](https://www.wearedevelopers.com/videos/100085-understanding-kubernetes-in-a-visual-way) - [Applying Agile Principles to Incident Management ](https://www.wearedevelopers.com/videos/101-applying-agile-principles-to-incident-management) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [Inside the AI Revolution: How Microsoft is Empowering the World to Achieve More](https://www.wearedevelopers.com/videos/869-inside-the-ai-revolution-how-microsoft-is-empowering-the-world-to-achieve-more) - [AI in Production: applied AI & enterprise use cases](https://www.wearedevelopers.com/videos/100130-ai-in-production-applied-ai-enterprise-use-cases) - [Instant KAI Sandboxes with vCluster: Multi-Tenant, Multi-Scheduler GPU Sharing](https://www.wearedevelopers.com/videos/100333-instant-kai-sandboxes-with-vcluster-multi-tenant-multi-scheduler-gpu-sharing) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Got AI ideas but no money? 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