We're hiring Senior Software Engineers to join our AI-native engineering team. You'll design, build, and operate production AI systems - including AI platform capabilities, agentic workflow infrastructure, and LLM-powered features that serve institutional financial clients. This is a hands-on individual contributor role for engineers who are deeply fluent in AI-native development and want to work at the intersection of applied AI and backend systems engineering.

What You'll Do :

Build and Operate AI Systems :

- Design, build, and ship production-quality backend services, APIs, and AI platform components used across multiple engineering teams.

- Build and integrate LLM-powered systems such as RAG pipelines, AI SDKs, evaluation workflows, guardrails, prompt/tool orchestration, and model observability.

- Improve the reliability, scalability, observability, and operational quality of production AI systems.

- Build internal tools, frameworks, automation, and documentation that improve developer productivity and AI capabilities.

- Participate in code reviews, design reviews, debugging, incident response, and operational support.

Drive Technical Excellence :

- Contribute to technical design for complex projects, including evaluating tradeoffs and proposing pragmatic implementation plans.

- Partner with product, design, and engineering teams to translate platform needs into well-designed technical solutions.

- Help identify and reduce technical debt, reliability risks, and friction in the software development lifecycle.

- Collaborate with Staff and senior engineers to establish reusable patterns and raise engineering standards.

Build with AI-Native Practices :

- Use agentic coding tools and LLM-assisted development as a primary part of your workflow - this is how the entire team operates.

- Critically evaluate AI-generated code for correctness, edge cases, and regressions - shipping quality output regardless of how it was produced.

- Contribute to the team's evolving practices around AI-accelerated development and testing.

Qualifications :

Required :

- 5+ years of experience designing, building, and operating production software systems.

- Strong backend engineering experience with Python frameworks such as FastAPI, Flask, or Django.

- Experience building or integrating AI/LLM-powered systems in production - such as RAG pipelines, AI SDKs, evaluation workflows, guardrails, or agentic workflows.

- Experience with relational/NoSQL databases, including schema design, query optimization, and data modeling.

- Experience with cloud-native technologies such as AWS, Docker, and Kubernetes.

- Strong understanding of CI/CD, observability, and operating services in production.

- Ability to break down complex technical problems and deliver pragmatic, maintainable solutions.

- Strong ownership mindset, with the ability to drive projects independently while collaborating effectively.

- Clear communication skills and the ability to explain technical tradeoffs to engineering and cross-functional partners.

- Hands-on experience with AI-native development tools (e.g., Cursor, Augment); demonstrated ability to embed AI-driven practices to accelerate velocity and code quality.

- Ability to critically evaluate AI-generated code and outputs, including identifying failure modes, regressions, and edge cases.

Preferred :

- Experience with document processing pipelines, structured extraction from unstructured documents, or vector stores.

- Familiarity with evaluation frameworks for LLM output quality (e.g., RAGAS, custom evals, human-in-the-loop review).

- Background in financial services or fintech.