Staff Backend Engineer, AI
Pulley
full-time
Posted on:
Location Type: Remote
Location: Remote • 🇺🇸 United States
Visit company websiteSalary
💰 $200,000 - $240,000 per year
Job Level
Lead
Tech Stack
AWSCloudDistributed SystemsDockerGoGoogle Cloud PlatformKubernetesMicroservicesPostgresPythonRedis
About the role
- Architect 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 vs. buy decisions
- Mentor engineers on backend best practices, system design, and technical decision-making
Requirements
- 7+ 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
- Demonstrated 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)
- Track 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
- Experience with Kubernetes, Docker, and cloud infrastructure (AWS/GCP) is a bonus
- Background in FinTech or regulated industries is a bonus
- Contributions to open-source projects or technical writing is a bonus
- Familiarity with AI-powered developer tools like Cursor or Copilot is a bonus.
Benefits
- Competitive 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)
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
GolangPythonAPI designmicroservices architectureevent-driven systemsasync workflowsdatabase optimizationdata processingconcurrency patternsprompt engineering
Soft skills
mentoringcollaborationtechnical decision-makingleadershipcommunication