Software Engineer III

LOS ANGELES CAPITAL MANAGEMENT LLC•Los Angeles, CA

9d•$130,000 - $155,000•Hybrid

About The Position

Reporting to the Director in the Quantitative Investment Platform (QIP) team within Research, the Software Engineer will help design, build, and maintain the Python applications, services, and tooling that power the Firm’s investment platform. As a senior engineer, this person will write production code — APIs, domain logic, automation, and supporting libraries — with a strong emphasis on clean, well-tested, maintainable software. This is a strong fit for someone with real depth in software engineering that wants to develop critical infrastructure, model, and data handling code in a quantitative investment firm.

Requirements

Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, Mathematics, Statistics, or equivalent professional experience
At least 5 years of hands-on professional experience writing production software
Solid proficiency in Python, including a working understanding of idiomatic, well-structured code
Familiarity with writing automated tests and an understanding of why testing matters.
Familiarity with version control in Git, including branching and the pull-request / code-review workflow
Understanding of core software engineering fundamentals: data structures, clean code, modular design, and debugging
Working proficiency in SQL
Demonstrated ability to learn new technologies quickly and a genuine eagerness to do so
Clear written and verbal communication, and the ability to work effectively on a collaborative team
Experience or strong interest in building with LLMs: MCP server development, agentic workflows, and frameworks such as LangChain/LangGraph and LangSmith for tracing and evaluation

Nice To Haves

Exposure to test-driven development and an interest in software craftsmanship (e.g., Clean Code, refactoring, working effectively with legacy code)
Experience building web APIs, ideally with FastAPI or a similar framework
Experience with data modeling and validation libraries such as Pydantic
Exposure to CI/CD pipelines (e.g., GitHub Actions) and modern deployment practices
Familiarity with Azure or another major cloud provider, and with containerization (Docker)
Exposure to a cloud data warehouse (ideally Snowflake) and workflow orchestration (Prefect, Dagster, Airflow)
Interest in financial markets, quantitative investing, or financial/market data

Responsibilities

Design, build, and maintain Python applications and services that support the firm’s research and investment process
Write clean, well-tested, maintainable code following team standards: type hints throughout, small focused functions, and clear naming
Build and consume internal APIs (e.g., FastAPI) and well-modeled domain libraries (e.g., Pydantic), with attention to clear interfaces and separation of concerns
Participate actively in code review, both giving and receiving feedback, as a core part of how the team ships software
Contribute to the team’s automated test suites and help keep them fast, reliable, and meaningful
Help maintain and improve CI/CD pipelines (GitHub Actions) so that changes ship safely and frequently
Integrate the software you build with the firm’s data platform (Snowflake) and orchestration (Prefect) where the work calls for it
Write and keep current the technical documentation and runbooks for the components you own
Collaborate with quantitative researchers and fellow engineers to turn requirements into reliable, well-designed software
Participate in agile team practices including sprint planning, backlog grooming, and estimation
Continuously sharpen your engineering practice and take on increasing scope and ownership as you grow
Build and extend AI-assisted tooling for the research and engineering workflow, including MCP servers and agent integrations (e.g., Claude, Anthropic API) that expose internal data and services to LLM-based assistant/agent.