Overview
Hands-on Staff Software Engineer providing technical leadership for the Forecasting and Recommendations platforms, with a focus on production-grade AI and agentic systems.
What you'll do
- Design, build, and operate systems supporting forecasting, recommendations, and agentic AI workflows in production.
- Write production-quality code daily; own services end-to-end from design through on-call and incident resolution.
- Architect low-latency, high-throughput SaaS services, including APIs, data pipelines, model inference, and agent orchestration.
- Build and maintain production-grade agentic applications, including tool-using agents, workflow orchestration, and guardrails.
- Work fluently with foundational LLMs (e.g., GPT, Claude, Gemini Pro), selecting appropriate models and deployment patterns based on latency, cost, and reliability tradeoffs.
- Use frameworks and tooling such as LangChain, voice agents, and related ecosystems to accelerate development while enforcing production discipline.
- Embrace AI-assisted development workflows (e.g., Cursor, GitHub Copilot, vibe coding paradigms) to move quickly without sacrificing quality.
- Champion observability and reliability: metrics, logging, tracing, alerting, and post-incident analysis.
- Lead and participate in production incident response, retrospectives, and systemic fixes.
- Identify architectural risks early and make design decisions that prevent outages and scalability issues.
- Reduce complexity across services, infrastructure, and processes to improve stability and team velocity.
- Provide technical guidance across teams and participate in architectural reviews beyond your immediate domain.
What you'll need
- 12+ years of professional software engineering experience building and operating production-grade distributed systems.
- A strong track record of hands-on ownership of business-critical services, including measurable improvements in latency, throughput, stability, or cost.
- Deep expertise in systems design, including service boundaries, concurrency, data modeling, failure handling, and scalability tradeoffs.
- Production experience supporting machine learning-driven systems (forecasting, recommendations, or similar), with emphasis on serving, pipelines, and infrastructure.
- Expert-level experience with AWS, including designing, deploying, and operating large-scale cloud-native systems.
- Strong hands-on experience with Kubernetes, containerized microservices, and modern CI/CD pipelines.
- Experience operating software in both on-prem data center and AWS cloud environments.
- Fluency with modern AI-assisted development tools (e.g., Cursor, GitHub Copilot) and comfort working in "vibe coding"-style workflows that favor fast iteration, tight feedback loops, and continuous refactoring.
- 2+ years of experience in Python and proficiency in one or more backend languages commonly used for large-scale systems (e.g., Python, Java, Go, Scala).
- Bachelor's or master's degree in computer science, Mathematics, or a related field, or equivalent practical experience.
Details
- Location: Remote, United States.
- Salary range: $220,000 - $240,000, depending on location and experience.
Read the full description and apply on the company’s own careers page.