Fidelity Investments

Fidelity Investments

Software Engineer - Python

Westlake, TX · Full-time

No sponsorshipDetected 10 hours ago
PythonJavaBashFastAPICode ReviewGitAWSCloud PlatformsDockerKubernetesTerraformCI/CDJenkinsLinuxPlatform EngineeringRESTMachine LearningControlspytest

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odds of building a lasting career here

37Risky
Cap-exempt (no lottery)0
Sponsors this role80
Entry-level history0
PERM / green-card track0
Lottery odds40
Fits your clock70

Thin sponsorship signal and lottery-bound. A low-probability bet with your clock running. Prioritize cap-exempt roles and proven entry-level sponsors first.

Lottery odds assume a STEM candidate.

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About the role

  • This role is ideal for engineers with a strong foundation in software development who are eager to grow their skills in cloud-native systems, data platforms, and AI/ML infrastructure.
  • The team focuses on providing reusable capabilities, standardized tooling, and efficient workflows that accelerate innovation across Fidelity.
  • You will work in a collaborative, fast-paced environment that emphasizes learning, ownership, and continuous improvement, while contributing to impactful solutions used across the enterprise.

Nice to have

  • Basic knowledge of Java (ability to work with an existing codebase)
  • Exposure to Kubernetes or container orchestration platforms
  • Familiarity with infrastructure-as-code tools such as Terraform
  • Experience with CI/CD tools (Jenkins or similar)
  • Experience writing clean, testable code (unit testing, mocking frameworks such as Pytest or unittest)
  • Familiarity with REST APIs and service-based architectures (e.g., FastAPI or similar frameworks)
  • Basic understanding of AWS services such as S3, IAM, Lambda, or container-based workloads
  • Understanding of Git workflows including branching strategies and pull requests

Visa & Work Authorization

  • Note: Fidelity will not provide immigration sponsorship for this position

This listing is sourced directly from Fidelity Investments's careers page and normalized into a canonical job model.