Oaktree is looking to embed AI into its product engineering processes to enhance speed, code quality, and creative problem-solving, ultimately shaping the future of Oaktree's digital platforms and ensuring products are reliable, powerful, expressive, and intuitive.
Requirements
- 10+ years of experience in software engineering.
- Proven success as a senior individual contributor or staff/principal engineer in enterprise or financial technology settings.
- Strong understanding of modern architectures (cloud-native, microservices, data-driven systems).
- Experience leveraging AI-assisted development and product tools for design, testing, and delivery.
- Hands-on experience with modern programming languages, frameworks, and DevOps toolchains.
- Skilled at mentoring engineers and influencing without authority.
- Excellent communicator who can think in both systems and stories.
Responsibilities
- Serve as a senior technical and product thought partner, translating business needs into high-quality engineering solutions.
- Lead design and implementation of key product capabilities—owning architecture, performance, and maintainability.
- Leverage AI-assisted development tools (e.g., GitHub Copilot, ChatGPT, and AI testing frameworks) to enhance speed, code quality, and creative problem-solving.
- Contribute to long-term product vision and platform architecture that enable scale, flexibility, and reusability.
- Advocate for the responsible use of AI in engineering workflows, emphasizing transparency, validation, and ethical data practices.
- Provide design reviews, code reviews, and architecture coaching to strengthen team craft.
- Implement modern development and release practices (CI/CD, feature flags, automated testing, AI-assisted QA).
Other
- This role is a senior individual contributor who combines deep technical expertise with strong product sense, AI fluency, and mentoring capability.
- This role will bring a holistic view of technology, user experience, and business value—embedding AI into how we think, build, and deliver.
- Bring a product mindset to engineering: define MVPs, experiment with solutions, iterate quickly, frame problems in terms of user value, prioritize impact, and simplify complexity; own discovery and roadmap planning to define feasible, high-value solutions.
- Flex into product management responsibilities as needed—helping to define product OKRs, shape roadmaps, and deeply understand user needs and workflows to ensure engineering efforts align with business outcomes.
- Communicate trade-offs clearly, framing technical choices in terms of business and user outcomes.
