Software Engineer, AI Platform
SoFi Technologies, Inc.
San Francisco, CA, United States
4 days ago
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Role details
Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Working hours
Regular working hours
Job source
Tech stack
AI Evaluation
Java (Programming Language)
Artificial Intelligence
Automation of Tests
Cloud Computing
Code Generation
Code Review
Computer Programming
Data Governance
Data Stores
Relational Databases
Programming Tools
+24 more
Fault Tolerance
Python (Programming Language)
Pair Programming
Prism (Software)
Software Deployment
Software Engineering
Software Technical Review
Data Logging
Retrieval-Augmented Generation
Large Language Models
Concurrency
Prompt Engineering
Backend
Kotlin
Integration Tests
Kubernetes
Information Technology
Low Latency
Api Design
Prompt Templates
Dynatrace
Docker
Golang
Microservices
Job description
In this role, you will pair hands-on software development with systems thinking. You will take technical ownership over feature delivery and key service components-translating partially defined technical problems into production-grade, highly available microservices. You will collaborate closely with partner teams (such as Autonomous Coding, CI/CD, and product squads), practice operational rigor, and use AI-assisted engineering tools responsibly to raise quality and delivery velocity across our engineering community.
What youβll do:
- Design, implement, test, deploy, and operate foundational components of Prism and contribute to the underlying components.
- Build and maintain telemetry, usage instrumentation, and reporting pipelines to provide clear visibility into Prism and the learning feedback loop.
- Lead technical feature execution for assigned platform work streams, breaking down complex tasks to parallelize implementation with teammates and aligning dependencies with product and engineering managers.
- Participate actively in technical design reviews, reasoning through architectural trade-offs (such as latency, fault tolerance, concurrency, and security) and documenting clear technical specifications.
- Contribute to team engineering quality by following and refining coding conventions, automated testing patterns, and reusable service templates.
- Drive operational excellence by automating test and deployment workflows, participating in on-call service ownership, acting as an incident resolver, and implementing post-incident remediations to prevent recurrence.
- Engage directly with internal customers to understand their day-to-day workflows, support adoption of Prism, and incorporate feedback into iterative system improvements.
- Mentor early-career engineers through thoughtful code reviews, constructive design feedback, and pair programming to foster continuous team growth., * Use AI tools responsibly to prototype solutions, navigate codebases, and accelerate implementation velocity while upholding high security and safety standards.
- Critically inspect and validate AI-generated code, backing all implementations with comprehensive automated tests to ensure long-term maintainability.
- Maintain rigorous compliance with data governance and security policies, ensuring sensitive member data and proprietary assets are never exposed to unapproved tools.
- Elevate team productivity by sharing effective harnesses, prompt templates, and operational guardrails.
Requirements
- Education & Minimum Experience Requirements: Bachelorβs Degree + 2-3 Years of Experience OR Masterβs Degree + 2 Years of programming experience in software engineering, computer science, or a related field.
- Proven programming proficiency in at least one modern backend language (such as Java, Kotlin, Python, Go, or Scala).
- Solid experience building and operating distributed backend services in a microservices or cloud environment, with an understanding of concurrency, fault tolerance, idempotence, and API design.
- Practical experience working with relational databases, persistent data stores, and data modeling concepts.
- Practical understanding of operational excellence: logging, metrics, distributed tracing, automated unit/integration testing, and safe production deployment practices (canarying, feature flags).
- Hands-on experience developing with or integrating AI-assisted developer tools, LLM APIs, prompt engineering patterns, or tool-execution frameworks.
- Collaborative approach with clear written and verbal communication skills, including the ability to write structured technical design documents and share constructive code review feedback., * Experience engineering internal developer platforms (IDP), developer tooling, or CLI workflows.
- Familiarity with container orchestration (Docker, Kubernetes) and modern CI/CD pipeline automation.
- Experience in fintech or within another highly regulated industry environment.
- Deep understanding of LLM integration, context retrieval architectures (RAG), and AI evaluation frameworks.
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