Staff Backend Engineer AI

OverviewStaff Backend Engineer responsible for architecting and building foundational systems that power our AI‑native product.ResponsibilitiesArchitect distributed systems that power AI agent orchestration, handling complex multi‑step workflows with reliability and observability.Design and implement core backend services in Golang for high‑performance, concurrent operations and Python for AI/ML integrations and data pipelines.Build robust APIs and service interfaces that abstract AI capabilities for consumption by multiple clients and internal systems.Own the technical roadmap for backend infrastructure supporting LLM integrations, vector search, and real‑time data processing.Establish architectural patterns and standards for service design, data modeling, and inter‑service communication.Drive system scalability and reliability, implementing caching strategies, database optimization, and async processing patterns.Build data pipelines that process equity data, embeddings, and user interactions to continuously improve AI model performance.Collaborate cross‑functionally to translate business requirements into technical architecture and make pragmatic build versus buy decisions.Mentor engineers on backend best practices, system design, and technical decision‑making.QualificationsTechnical Foundation7+ years of backend engineering experience building production systems at scale.Expert‑level proficiency in Python for AI/ML integrations, data processing, and scripting.Strong Python skills with deep understanding of concurrency patterns, performance optimization, and production Go services.Proven experience designing and building distributed systems, including microservices architecture, event‑driven systems, and async workflows.Deep knowledge of API design (REST) and service‑to‑service communication patterns.AI Infrastructure ExperienceDemonstrated experience building backend systems that integrate LLMs and AI capabilities into production applications.Hands‑on work with agent frameworks, LLM orchestration, and AI service reliability.Familiarity with RAG architectures, vector databases (Pinecone, Weaviate, Qdrant), and embeddings pipelines.Experience building evaluation frameworks and observability for AI systems.Understanding of prompt engineering and LLM API optimization (latency, costs, rate limits).System Design & LeadershipTrack record of architecting greenfield services from concept to production with scalability and maintainability in mind.Experience with database design and optimization (PostgreSQL, Redis, time‑series databases).Strong foundation in system observability, monitoring, and debugging distributed systems in production.Proven ability to lead technical initiatives and establish engineering best practices.Experience mentoring engineers and elevating team technical capabilities.Bonus PointsExperience with Kubernetes, Docker, and cloud infrastructure (AWS/GCP).Background in FinTech or regulated industries.Contributions to open‑source projects or technical writing.Familiarity with AI‑powered developer tools like Cursor or Copilot.BenefitsCompetitive salary and equity.Medical, Dental, and Vision insurance.Unlimited PTO + Winter holiday break.Parental leave.Generous stipends for WFH, learning, wellness, and AI tools.401(k) match (US) / Pension match (Canada).Annual Salary Range$200,000—$240,000 USD #J-18808-Ljbffr