Staff Software Engineer (AI)

Juniper Square•,

21h•$210,000 - $260,000•Hybrid

About The Position

We're hiring Staff Software Engineers to join our AI-native engineering team. At the Staff level, you are a technical leader - setting technical direction, driving architectural decisions, and raising engineering quality across your team. You will own the strategy and hands-on delivery of AI systems that power core product experiences for institutional financial clients, spanning AI platform infrastructure, agentic workflows, and LLM-powered features. This is a player-coach role for engineers who lead through code and architecture, not just direction. Own Technical Direction and Architecture • Set the technical direction for AI systems - including shared AI SDKs, guardrails, evaluation frameworks, feedback systems, and agentic workflow infrastructure • Own architecture and technical strategy for complex backend and AI platform systems, from design through production • Lead technical design for ambiguous, cross-functional initiatives - evaluating tradeoffs, aligning stakeholders, and driving implementation • Evaluate and select technologies with a bias toward what ships well and scales sustainably Build and Operate AI Systems • Write production code as a hands-on individual contributor - this is not a role that delegates implementation to others • Design and operate LLM-powered systems: RAG pipelines, agentic workflows, evaluation infrastructure, guardrails, and model observability • Own end-to-end reliability of AI systems from design through structured output delivery • Define quality benchmarks, evaluation frameworks, and feedback loops to continuously improve AI output accuracy and system reliability Champion AI-Native Development • Champion and embed AI-native development practices and tools (e.g., Cursor, Augment) to achieve significant productivity gains across the team • Foster a culture of rapid iteration, high velocity, and quality - including guiding the effective use of AI code generation • Bring strong, informed opinions about how to get the most from AI-assisted development while maintaining reliability and correctness Lead and Grow the Team • Mentor engineers, raise the quality of technical decision-making, and help the team execute with consistency • Establish coding standards, review practices, and architectural documentation that scale as the team grows • Help define what "good" looks like for a team building at speed without sacrificing quality • Partner with recruiting to build and grow the team Collaborate Cross-Functionally • Work closely with engineering managers, product, design, and QA to translate requirements into executable technical plans • Participate actively in design reviews and roadmap discussions with grounded, implementation-level perspective • Handle most cross-team conflicts and technical decisions autonomously

Requirements

7+ years of backend and/or ML engineering experience with a trajectory of increasing technical leadership, architectural responsibility, and mentorship
A portfolio of shipped production systems - we will ask you to walk through specific technical decisions you personally made and code you personally wrote; this is not a role for someone whose primary contribution has been directing others
Deep expertise in Python, with strong proficiency in building production-grade backend services; experience with other server-side languages (Node/TS, Java) a plus
Production experience building and operating AI/LLM-powered systems — such as AI SDKs, RAG pipelines, evaluation frameworks, agentic workflows, or model observability — in real systems, not just experimentation
Experience leading technical design for complex systems, including making architecture decisions, evaluating tradeoffs, and guiding implementation across multiple engineers or teams
Experience with relational/NoSQL databases, including schema design, performance tuning, and data modeling
Experience building and operating cloud-native systems using AWS, Docker, Kubernetes, and infrastructure as code
Strong understanding of CI/CD, observability, reliability, and operational excellence in production environments
Ability to work through ambiguity, break down complex problems, and drive alignment across engineering, product, and design
Demonstrated ability to raise engineering quality through technical standards, design reviews, mentoring, and reusable platform patterns
Hands-on experience with AI-native development tools (e.g., Cursor, Augment); demonstrated ability to embed AI-driven practices to accelerate team velocity and code quality
Ability to critically evaluate AI-generated code and outputs, including identifying failure modes, regressions, and edge cases

Nice To Haves

Experience with document processing pipelines, structured extraction, or vector stores
Familiarity with MLOps tooling, experiment tracking, or model deployment pipelines
Background in financial document processing or fintech data pipelines
Prior experience in a technical lead or TLM capacity on a new or early-stage product team

Responsibilities

Set the technical direction for AI systems - including shared AI SDKs, guardrails, evaluation frameworks, feedback systems, and agentic workflow infrastructure
Own architecture and technical strategy for complex backend and AI platform systems, from design through production
Lead technical design for ambiguous, cross-functional initiatives - evaluating tradeoffs, aligning stakeholders, and driving implementation
Evaluate and select technologies with a bias toward what ships well and scales sustainably
Write production code as a hands-on individual contributor - this is not a role that delegates implementation to others
Design and operate LLM-powered systems: RAG pipelines, agentic workflows, evaluation infrastructure, guardrails, and model observability
Own end-to-end reliability of AI systems from design through structured output delivery
Define quality benchmarks, evaluation frameworks, and feedback loops to continuously improve AI output accuracy and system reliability
Champion and embed AI-native development practices and tools (e.g., Cursor, Augment) to achieve significant productivity gains across the team
Foster a culture of rapid iteration, high velocity, and quality - including guiding the effective use of AI code generation
Bring strong, informed opinions about how to get the most from AI-assisted development while maintaining reliability and correctness
Mentor engineers, raise the quality of technical decision-making, and help the team execute with consistency
Establish coding standards, review practices, and architectural documentation that scale as the team grows
Help define what "good" looks like for a team building at speed without sacrificing quality
Partner with recruiting to build and grow the team
Work closely with engineering managers, product, design, and QA to translate requirements into executable technical plans
Participate actively in design reviews and roadmap discussions with grounded, implementation-level perspective
Handle most cross-team conflicts and technical decisions autonomously