Senior Software Development Engineer

Capital Group•Los Angeles, CA

About The Position

We are seeking a strong senior software engineer to design, build, and operate enterprise platforms and integration systems that power Capital Group's investment technology capabilities. You will work closely with engineering partners, product teams, and investment professionals to translate complex business needs into reliable, scalable, production-grade systems. This role emphasizes engineering rigor, system design, developer experience, and delivering durable platforms that teams across the organization depend on. You will join a high-performing team building data platforms, enterprise integrations, and developer tooling — connecting systems like Databricks, Snowflake, Dremio and internal applications into cohesive, well-governed workflows. We value craftsmanship in software engineering, thoughtful problem solving, and a strong sense of ownership.

Requirements

8+ years of professional software engineering experience, with strong proficiency in one or more modern languages (Python, TypeScript/Node.js, Java, or similar).
Demonstrated experience designing and building large-scale production systems with solid architectural foundations.
Strong understanding of system design principles: APIs, distributed systems, event-driven architectures, and cloud-native development (Azure preferred).
Hands-on experience building integration layers across enterprise platforms and data systems.
Strong fundamentals in software design: object-oriented and functional patterns, testing strategies, CI/CD, infrastructure-as-code, and observability.
Strong problem-solving ability — able to break down ambiguous problems into clear technical plans with milestones and trade-offs.
Proven ability to own projects independently and drive them to completion.
Strong communication skills and behavioral maturity; able to collaborate effectively with diverse stakeholders across engineering, product, and business.

Nice To Haves

Experience building developer platforms, internal tooling, or self-service infrastructure that other teams consume.
Familiarity with data platforms such as Databricks, Unity Catalog, Dremio, or similar enterprise data ecosystems.
Experience with enterprise integration patterns — Claude, OpenAI.
Exposure to AI/ML-adjacent systems — not as an ML practitioner, but as the engineer building the platforms and infrastructure that ML systems run on.
Experience in financial services, investment workflows, or regulated enterprise environments where data accuracy, security, and auditability are non-negotiable.

Responsibilities

Design and implement scalable, production-quality platforms and services — distributed systems, APIs, and cloud-native architectures.
Take end-to-end ownership of technical projects, from system design through implementation, deployment, and operational excellence.
Build integration layers across heterogeneous enterprise systems — connecting data platforms, collaboration tools, and proprietary applications through APIs, SDKs, and protocol adapters.
Build developer platforms and internal tooling — CLI frameworks, plugin systems, automation infrastructure, or self-service capabilities that multiply team productivity.
Maintain a high bar for code quality, testing, documentation, and reliability.
Contribute to architectural decisions, ensuring systems are maintainable, extensible, and resilient.
Operate with urgency, ownership, humility, and strong collaboration across teams.