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.
About the role
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.
What you’ll do
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
What we’re looking for
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
Nice to have (not required)
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
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