Cloud/AI Engineer
Skills
Computer ScienceDevopsApplication EngineeringData IntegrityData WarehousingDatabasesEmerging Technologies
What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- Bachelor's degree in Computer Science Engineering or related technical field
- 20+ years cloud engineer experience
- 3+ years AI engineer experience
- Enterprise-scale solution delivery in public and private sectors
- Hands-on cloud engineering and full stack software development
- Experience with Docker Kubernetes serverless and AWS Azure or Google Cloud
- Data warehouse migration experience with schema conversion and validation
- Strong proficiency in Python JavaScript TypeScript React FastAPI SQL Spark PySpark and REST APIs
- Experience with CI/CD DevOps Terraform CloudFormation and platform engineering
- Experience integrating enterprise systems through APIs event-driven architectures and distributed services
- Ability to architect secure scalable resilient cloud systems with governance auditability data protection and access controls
- Hands-on Generative AI experience including LLMs RAG agentic AI semantic search and vector databases
- Experience managing AI lifecycle in cloud environments with MLOps tooling
- Ability to collaborate with stakeholders and translate requirements into technical solutions
- Experience delivering mission-critical applications in regulated environments
- Strong analytical problem-solving and systems-thinking skills
Nice to have
- Technical leadership
- Mentoring
- Systems thinking
- Analytical mindset
- Collaborative
Day to day
- Design, develop, deploy, and sustain secure cloud-native and AI solutions for FAA mission objectives.
- Lead modernization of legacy systems and enterprise platforms through cloud transformation and application refactoring.
- Collaborate with government stakeholders and technical teams to deliver innovative, compliant, mission-critical technology solutions.