12097 AI Engineer - Solutions & LLMOps
About The Position
The AI Engineer role combines hands-on AI engineering and LLMOps responsibilities to help establish scalable, secure, and production-ready AI capabilities across the enterprise. The AI Engineer is responsible for evaluating, prototyping, designing, developing, deploying, supporting, and continuously improving enterprise AI solutions across a rapidly evolving technology landscape. This role is responsible for building AI-powered applications using enterprise AI platforms and cloud services while ensuring deployed solutions remain reliable, secure, and operationally efficient throughout their lifecycle. Additionally, the role supports AI operationalization, deployment automation, monitoring, prompt and model lifecycle management, LLMOps practices, and the ongoing maintenance and support of production AI solutions.
Requirements
- Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field
- 2+ years of experience in software engineering, cloud engineering, AI/ML development, or platform engineering
- Experience developing cloud-based applications, APIs, or automation workflows
- Experience with scripting or programming languages such as Python
- Understanding of cloud platforms, APIs, and application integration concepts
- Strong analytical, problem-solving, and collaboration skills
- Compliance with the Department of Energy's regulation 10 CFR 810 is required.
Nice To Haves
- Experience with AI, Machine Learning, Generative AI, or intelligent automation technologies
- Familiarity with cloud AI platforms such as Azure OpenAI, Azure AI Services, AWS Bedrock, or similar technologies
- Exposure to AI agents, copilots, Retrieval-Augmented Generation (RAG), or GenAI workflows
- Experience with DevOps, CI/CD, containerization, monitoring, LLMOps, MLOps concepts
- Experience with Git, Azure DevOps, GitHub, Docker, Kubernetes, or cloud-native development tools
- Familiarity with enterprise platforms such as ServiceNow, SAP, or Salesforce
- Experience within regulated industries such as utilities, energy, financial services, or healthcare
Responsibilities
- Develop proof-of-concept (POC) solutions for enterprise AI and Generative AI use cases
- Build AI agents, copilots, workflows, APIs, and AI-enabled applications using enterprise AI platforms and cloud services
- Experiment with emerging AI technologies and validate solution feasibility with business and technical teams
- Stay current on evolving AI engineering, GenAI, and MLOps trends and best practices
- Develop reusable AI services and shared components
- Develop and integrate AI solutions across enterprise platforms and cloud services
- Support reusable AI frameworks, integration patterns, and engineering best practices
- Contribute to scalable AI platform architecture and deployment standards
- Deploy, monitor, maintain, and optimize AI solutions in production environments
- Support CI/CD, deployment automation, versioning, lifecycle management, and release processes
- Implement monitoring, logging, observability, and performance tracking for AI applications
- Collaborate with infrastructure and platform teams to improve reliability, scalability, and operational excellence
- Ensure AI solutions comply with enterprise governance, cybersecurity, privacy, and Responsible AI standards
- Support governance reviews, risk assessments, and implementation of operational controls
- Incorporate security, monitoring, and lifecycle management into AI solution delivery
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
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Mid Level
