Sr Software Engineer - Full Stack Finance
Indexed description
This is an applied engineering role : you’ll build production ready services, UIs, and data flows using modern AI (LLMs, RAG, agents) rather than doing pure research.
Responsibilities
What You’ll Be Doing
- Partner with Finance and People & Culture to understand current workflows (e.g., forecasting, close/reconciliations, headcount planning, hiring funnel, manager self service) and reimagine them with AI
- Design and ship LLM powered and RAG based features (e.g., natural language queries over metrics, narrative insights, anomaly explanations, draft responses) in production applications
- Build and operate fullstack solutions (APIs, services, and UIs) using Java, JavaScript/React, and Python on cloud infrastructure (GCP preferred), including designing responsive, accessible React interfaces for Finance and People & Culture workflows
- Design and maintain data flows that combine financial, HR, and operational data into trustworthy metrics and AI ready datasets
- Create reusable AI patterns and components (prompts, agents, data access layers, evaluation approaches) that Finance and People & Culture can reuse across use cases
- Define and track success metrics for AI features (e.g., hours saved, cycle time reduction, forecast/headcount plan accuracy, adoption) and iterate based on results
- Apply TDD, automated testing (frontend and backend), code reviews, and CI/CD to keep services and UIs reliable, observable, and easy to change
- Protect sensitive financial and people data, including applying appropriate AI guardrails (data classification, access control, prompt/response logging)
- This job description in no way implies that the duties listed here are the only ones that team members can be required to perform
- BS in Computer Science or related field, or equivalent experience
- 5+ years building backend services and/or APIs in Java or Python
- 5+ years building frontend experiences with JavaScript/React , HTML, and CSS/SASS
- Strong SQL skills and experience designing schemas for analytics/metrics workloads
- Experience building and operating production services in a major cloud (GCP preferred) with modern CI/CD and Git workflows
- Solid understanding of object oriented design, data structures, algorithms, and Agile delivery
- Experience writing automated tests and working in a code review culture
- Strong communication skills; able to explain technical tradeoffs to nontechnical partners
- Experience working with finance, FP&A, or revenue operations teams and familiarity with common SaaS metrics (e.g., ARR, MRR, churn, NRR, pipeline, retention)
- Experience with data pipelines/ETL and analytics tooling (e.g., dbt, FiveTran, Airflow, Kafka, BigQuery, Snowflake, or similar)
- Experience applying AI/ML in production systems (e.g., LLMs, embeddings, vector databases, anomaly detection, forecasting)
- Familiarity working with artifact repositories such as JFrog or Cloudsmith
- Familiarity with Docker and Kubernetes
- Experience working with Google Cloud Platform (preferred) or another major cloud provider
- Familiarity with Terraform and infrastructureascode best practices
- Experience with a feature flag tool such as LaunchDarkly
- Experience writing QA automated tests and partnering closely with QA/Testing teams
- The physical activities of this position include frequent sitting, telephone communication, and working on a computer for extended periods. Visual acuity is required to perform activities close to the eyes.
- Team members are expected to maintain a dedicated and ergonomically appropriate remote workspace.
- Team members who live within commuting distance of one of our office locations (Greater Cincinnati/Northern Kentucky or Atlanta, Georgia) are expected to work in a hybrid capacity, with regular in-office presence as determined by the team or department.
- All team members must reside and perform their work within the United States.
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