Staff Full-Stack Engineer, Remote Eligible

Relha LLC

Cambridge (MA)

Remote

USD 245,000 - 335,000

Full time

8 days ago
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Job summary

Capital One in Cambridge, MA is seeking a Staff Software Engineer, Full Stack, with remote eligibility. You will lead as a trusted technical contributor, shaping architectures, mentoring engineers, and driving AI-native engineering practices across Finance Technology.

The role emphasizes delivering scalable, high-performance systems for liquidity management, predictive analytics, and financial planning infrastructure, while collaborating with AI/ML teams, data scientists, and product managers.

Qualifications

  • Bachelor's or higher degree in a technical field; relevant experience counts toward qualification.
  • Strong background in software architecture, distributed systems and ML/AI lifecycles.
  • Proven ability to design scalable, high-performance, cloud-based software solutions.

Responsibilities

  • Articulate and evangelize a bold technical vision for your domain.
  • Decompose complex problems into practical, scalable solutions.
  • Ensure quality of technical design and implementation.
  • Serve as an authoritative expert on non-functional system characteristics.
  • Continue learning and injecting advanced technical knowledge into our community.
  • Lead multiple projects simultaneously to maximize impact.
  • Mentor engineers and help strengthen organizational technical expertise.
  • Lead POC development for emerging AI frameworks and patterns.
  • Collaborate across towers to share architectures and raise bar company-wide.
  • Champion AIOps practices, driving reliability via AI-assisted monitoring and remediation.

Skills

Software architecture
Distributed systems
ML/AI development
Full stack development

Education

Bachelor's Degree
Master's Degree

Tools

Cloud platforms
CI/CD tooling

Job description

Capital One in Cambridge, MA is seeking a Staff Software Engineer, Full Stack, with remote eligibility. You will lead as a trusted technical contributor, shaping architectures, mentoring engineers, and driving AI-native engineering practices across Finance Technology.

The role emphasizes delivering scalable, high-performance systems for liquidity management, predictive analytics, and financial planning infrastructure, while collaborating with AI/ML teams, data scientists, and product managers.

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