
Full-Stack Cloud Engineer – Change Management Service
Vidorra Consulting Group
Job description
Full-Stack Cloud Engineer Change Management Service
Onsite in Mountain View, CA
About The Role
We are looking for an AI-native, full-stack cloud engineer to support and evolve our Change Management Service a critical platform governing how changes are deployed safely across the organization.
You will combine strong coding skills with deep AWS infrastructure knowledge, providing run-the-business (RTB) support while contributing meaningfully to feature development, tech refresh, and security initiatives.
Key Responsibilities
-
Provide on-call and RTB support for the Change Management Service.
-
Contribute to feature development across the full stack.
-
Drive and support tech refresh and security initiatives.
-
Troubleshoot issues across application, infrastructure, and deployment layers.
-
Champion engineering quality, testing, and operational best practices.
-
Collaborate with distributed teams on roadmap delivery.
Tech Stack
-
Languages: Go (Golang), Python, Java, Scala
-
AWS services: Lambda, CloudWatch, VPC, and related infrastructure
-
Cloud deployment pipelines and infrastructure-as-code practices
-
Observability, on-call, and incident tooling
Required Skills & Experience
-
5 10 years of professional software engineering experience, ideally on cloud-native services.
-
Proven, verifiable results delivering and operating production cloud services e.g., shipped features with demonstrable impact, measurable reliability gains, or successful security/tech-refresh programs.
-
Strong programming skills in Go and Python; Java or Scala a plus.
-
Deep understanding of AWS cloud deployment at the infrastructure and engineering level.
-
Comfortable with cloud infrastructure fundamentals (Lambda, VPC, deployment flows).
-
Very comfortable with on-call rotations and RTB operations.
-
Passionate about engineering quality and mindful use of modern tooling.
-
Experience building and/or leveraging AI agents (e.g., agentic workflows, LLM-based automation, AI-assisted engineering tools) to improve productivity and outcomes.
What We Look For
-
Strong sense of ownership takes end-to-end responsibility for outcomes, not just tasks.
-
Self-motivated and proactive; able to operate independently with minimal supervision.
-
A good team player who collaborates effectively across teams, geographies, and time zones.
-
Proven track record of delivering measurable results in previous roles.