Backend Engineer

Job Description

Job Description

We are hiring on behalf of a venture-backed AI startup building intelligent software that automates complex business workflows.

The platform uses large language models, proprietary data, and human-in-the-loop systems to complete work that previously required significant manual effort. Its backend systems power AI agents, customer integrations, data processing, evaluation infrastructure, and production workflows.

The company is hiring a Backend Engineer to build the reliable systems behind its AI products.

As a Backend Engineer, you will design and build the services, APIs, data models, and infrastructure that power the company’s product.

You will work primarily in Python and PostgreSQL while collaborating closely with product engineers, AI engineers, customers, and company leadership.

This is not a narrow API-development role. You will work on production architecture, data systems, model integrations, security, reliability, and product capabilities.

• Design, build, and maintain production backend services using Python
• Develop APIs that support customer-facing applications and AI workflows
• Design scalable relational data models using PostgreSQL
• Build integrations with model providers, customer systems, and third-party platforms
• Develop systems for asynchronous jobs, event processing, and long-running AI workflows
• Deploy and operate services using AWS
• Debug production issues across application, data, model, and infrastructure layers
• Help shape backend architecture and engineering practices as the company grows

• Approximately 2–9 years of professional software engineering experience
• Strong professional experience with Python
• Experience designing and operating production APIs or backend services
• Strong understanding of relational databases, SQL, and data modeling
• Experience with PostgreSQL or a comparable production database
• Familiarity with AWS, GCP, or another major cloud platform
• Understanding of application security, authentication, and authorization
• Experience debugging and operating systems in production
• Ability to independently own technical projects from design through deployment
• Comfort making pragmatic engineering decisions in an early-stage environment
• Strong communication and cross-functional collaboration skills

• Experience building AI, LLM, agent, or machine-learning infrastructure
• Experience integrating OpenAI, Anthropic, or other model providers
• Familiarity with LLM evaluation, retrieval, embeddings, or vector databases
• Experience with Docker, Kubernetes, Terraform, or CI/CD systems
• Experience with Redis, Kafka, queues, or event-driven architectures
• Experience building multi-tenant SaaS products
• Previous experience at an early-stage startup
• Experience with data-intensive or distributed systems