Senior Cloud and AI Infrastructure Engineer
About The Position
As a Senior Cloud and AI Infrastructure Engineer, you will work within a highly collaborative, multi-functional team committed to improving the value of our technology solutions. The team blends deep technology and business expertise with a passion for exploring and implementing new emerging technologies while working in an open and transparent way. We are passionate about opensource contribution, sharing our expertise and knowledge with the engineering community, participating in foundations like the CNCF, CDF and FINOS while embracing a continuous learning approach support by a dedicated learning day each week. This is an opportunity for a highly motivated Cloud Engineer to join Fidelity Architecture and Engineering (FAE) and work in a diverse, open and transparent culture where you will contribute to powering the next generation of Fidelity’s digital services through innovative solutions using the latest cloud native technologies and leading-edge engineering practices.
Requirements
- Experience with LLM application patterns such as prompt engineering, retrieval-augmented generation (RAG), tool use, model evaluation, guardrails, and autonomous/agentic workflows.
- Strong experience deploying and operating cloud-native applications in AWS, especially EKS, EC2, and related platform services.
- Hands-on experience with infrastructure as code and platform automation using tools such as CloudFormation, Helm, OpenTofu/Terraform, and GitOps-style workflows.
- Strong software engineering skills with hands-on experience in one or more languages, with Python as a primary language.
- Experience building and operating CI/CD pipelines using tools such as GitHub Actions, Jenkins, Artifactory, and SonarQube.
- Understanding of security, compliance, and responsible AI practices, including secure handling of enterprise data, secrets, access controls, and AI governance.
- Strong communication and collaboration skills, with the ability to partner across engineering, security, platform, and developer experience teams.
- Passion for emerging AI technologies, continuous learning, and fostering a DevOps/platform engineering culture.
Nice To Haves
- Experience with Bedrock and/or SageMaker preferred.
- Additional experience in Go, Rust, and/or TypeScript/Angular preferred.
- Working knowledge of Model Context Protocol (MCP) and how it is used to connect models and agents to enterprise tools and services.
- Experience deploying and operating GenAI agents or multi-agent systems in production.
- Experience with LLMOps / AI platform engineering, including evaluation pipelines, model observability, prompt/version management, and usage/cost tracking.
- Relevant certifications such as AWS Certified Solutions Architect, AWS Machine Learning Specialty, CKA, or equivalent cloud/platform credentials.
- Experience building and deploying generative AI applications and developer productivity tooling in enterprise environments.
Responsibilities
- Deploying and operating cloud-native applications in AWS, especially EKS, EC2, and related platform services.
- Hands-on experience with infrastructure as code and platform automation using tools such as CloudFormation, Helm, OpenTofu/Terraform, and GitOps-style workflows.
- Building and operating CI/CD pipelines using tools such as GitHub Actions, Jenkins, Artifactory, and SonarQube.
- Understanding of security, compliance, and responsible AI practices, including secure handling of enterprise data, secrets, access controls, and AI governance.
- Fostering a DevOps/platform engineering culture.
Benefits
- Dedicated learning day each week
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
Number of Employees
101-250 employees
