Senior Full-Stack AI Application Engineer - Backend, Database & API Emphasis
About The Position
AST SpaceMobile is building the first and only global cellular broadband network in space to operate directly with standard, unmodified mobile devices based on our extensive IP and patent portfolio and designed for both commercial and government applications. Our engineers and space scientists are on a mission to eliminate the connectivity gaps faced by today’s five billion mobile subscribers and finally bring broadband to the billions who remain unconnected. Position Overview We are seeking a Senior Full‑Stack AI Application Engineer (Backend & API Focus) to architect, build, and scale the backend platforms and APIs that power enterprise‑grade AI applications. In this role, you will design the service layer that connects machine learning models to web, mobile, and partner‑facing products—ensuring AI capabilities are reliable, performant, and securely consumable across multiple systems. This position is ideal for an engineer who thrives at the intersection of AI systems, backend architecture, databases, and API engineering, and who enjoys building foundational platforms that support a wide range of AI‑driven applications.
Requirements
- Bachelor’s degree in Computer Science, Software Engineering, or a related technical field
- Equivalent professional experience may be considered in lieu of formal education
- A minimum of 5 years of professional backend or full‑stack engineering experience
- Demonstrated experience designing and operating production‑grade APIs
- Strong interpersonal skills and ability to collaborate effectively within cross‑functional teams
- Excellent written and verbal communication skills
- Ability to translate complex technical requirements into clear, maintainable system designs
- Meticulous attention to detail to ensure reliability, security, and performance of production systems
- Strong ownership mindset and problem-solving ability in fast‑paced environments
- Backend frameworks and languages (e.g., Python, Go)
- API technologies (REST, WebSockets, GraphQL, gRPC)
- Relational and non‑relational databases (e.g., PostgreSQL, caching layers, time‑series or vector databases)
- Containerization and orchestration (Docker, Kubernetes)
- MLOps and model serving tools integrated with backend services
- Cloud infrastructure, monitoring, and logging platforms
- Ability to work in a standard office or remote environment
- Ability to use a computer and multiple monitors for extended periods
- Ability to participate in design discussions, code reviews, and collaborative meetings
Nice To Haves
- Experience building or supporting AI or ML‑powered applications in production
- Background developing platforms consumed by both web and mobile applications
- Experience with event-driven or streaming architectures
- Exposure to multi‑tenant or B2B API platforms
- Experience working in complex, highly integrated system environments
Responsibilities
- Design and build AI‑powered backend services and APIs that serve machine learning inference to web applications, mobile applications, and partner integrations
- Architect and implement an MLOps‑integrated model serving layer, supporting versioned deployments, automated rollouts, performance monitoring, and controlled experimentation
- Design API gateways and orchestration layers that coordinate between AI services, data sources, and downstream applications
- Define and implement clean, consistent API contracts optimized for web, mobile, and real‑time clients (REST, streaming, and event‑driven interfaces)
- Architect and maintain scalable database schemas and data models for application state, analytical workloads, and AI‑generated outputs
- Build and maintain backend data pipelines that ingest and process high‑volume operational and telemetry‑style data
- Implement authentication, authorization, and role‑based access control across backend services with auditability and secure access patterns
- Develop event‑driven backend components to support real-time updates, notifications, and cross-system synchronization
- Optimize backend and database performance for low‑latency inference, high‑throughput data ingestion, and responsive dashboards
- Collaborate with ML, frontend, and mobile teams to ensure seamless integration of AI capabilities into user-facing products
- Support scalable deployment using containerized microservices and cloud‑based infrastructure
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Number of Employees
1-10 employees
