Staff Software Engineer, Forecasting

Role

Hands-on Staff Software Engineer responsible for technical leadership of Forecasting and Recommendations platforms, focusing on production-grade AI and agentic systems. The role centers on designing, building, and operating high-throughput, low-latency distributed services that support forecasting, recommendations, model inference, and agent orchestration.

Key Responsibilities

• Design, build, and operate systems supporting forecasting, recommendations, and agentic AI workflows in production.
• Write production-quality code and own services end-to-end, including design, on-call responsibilities, 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.
• Select and deploy foundational LLMs (e.g., GPT, Claude, Gemini Pro) with attention to latency, cost, and reliability tradeoffs.
• Use frameworks and tooling such as LangChain and voice agents while enforcing production discipline.
• Embrace AI-assisted development workflows (e.g., Cursor, GitHub Copilot) and vibe-coding paradigms for fast iteration.
• Champion observability and reliability via metrics, logging, tracing, alerting, and post-incident analysis.
• Lead incident response, retrospectives, and implement systemic fixes; identify and mitigate architectural risks.
• Simplify system complexity to improve stability and team velocity and provide technical guidance across teams.

Requirements

• 10+ years of professional software engineering experience building and operating production-grade distributed systems.
• Demonstrated hands-on ownership of business-critical services with measurable improvements in latency, throughput, stability, or cost.
• Deep expertise in systems design: service boundaries, concurrency, data modeling, failure handling, and scalability tradeoffs.
• Production experience supporting ML-driven systems (forecasting, recommendations, or similar), emphasizing serving, pipelines, and infrastructure.
• Expert-level experience with AWS for 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 centers and AWS cloud environments.
• Fluency with AI-assisted development tools (e.g., Cursor, GitHub Copilot) and comfort with vibe-coding workflows.
• Proficiency in one or more backend languages used for large-scale systems (e.g., Python, Java, Go, Scala).
• Bachelor’s or master’s degree in computer science, mathematics, or related field, or equivalent practical experience.

Staff-level Expectations

• Be a prolific, hands-on contributor who raises the bar by example.
• Own and deeply understand large portions of codebase and system architecture.
• Simplify complex systems to increase velocity and reliability and set short- to medium-term technical direction (6–12 months) for the domain.
• Influence standards and architectural decisions across teams and ship multiple large services, shared libraries, or major infrastructure improvements.

Benefits

• Unlimited PTO
• Excellent medical, dental, and vision coverage
• Employee equity
• Employee discounts
• Virtual wellness classes
• Pet insurance

Salary

• $200,000 - $230,000, depending on location and experience.