Automation Developer - Service Enablement

AST SpaceMobile•Lanham, MD

4d•Onsite

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. We are seeking a talented and motivated Automation Developer to join the Service Enablement automation team, designing, developing, and maintaining automation frameworks, dashboards, data pipelines, and test tools that support satellite, gateway, and LTE end-to-end system analytics, quality, monitoring, and required action based on collected telemetry. This person works closely with R&D and Operations teams to improve system robustness, test coverage, quality, and operational readiness, bringing strong Python skills as the technical foundation for the role.

Requirements

B.Sc. in Computer Engineering, Software Engineering, Computer Science, or a related field.
At least 4 years of hands-on experience in automation development.
Experience in telecommunications, satellite, or network systems.
Experience developing automation for embedded systems, RF systems, communication systems, hardware interfaces, or complex test environments.
Strong understanding of end-to-end service lifecycle.
Proficient in Python.
Experience with REST APIs, data parsing, automation scripts, structured logs, and report generation.
Experience with version control tools such as Git.
Experience with CI tools such as Jenkins, GitLab CI, or similar platforms.
Familiar with RF equipment such as spectrum analyzers and signal generators.
Hands-on experience integrating AI agents (LLM-based) into automation and test workflows, for example log triage, failure analysis, test generation, and report drafting.
Experience developing tools and servers for agents using the Model Context Protocol (MCP) or equivalent tool/function-calling interfaces, exposing internal systems such as lab equipment, databases, dashboards, and CI as agent-callable tools.
Ability to design agentic workflows that are cost- and token-efficient, including right-sizing the model per task, context and prompt optimization, caching and batching, and preferring deterministic code over model calls where possible.
Experience with AI-assisted development tools such as Claude Code, Cursor, or GitHub Copilot to accelerate delivery.
Familiarity with evaluation and observability for AI systems, including regression tests for prompts and agents, tracing of agent runs, and usage/cost monitoring.
Awareness of data-security and privacy considerations when connecting LLMs to internal or customer data.
Strong problem-solving skills and high attention to detail.
Ability to work independently while coordinating with multiple engineering owners.
Team player with strong communication skills.
Comfortable creating clear technical documentation, test reports, and operational instructions.
Able to turn analysis results into clear visual output.
Fluent in English, both spoken and written.

Nice To Haves

SQL and database experience.
Experience with dashboards, databases, cloud services, or data platforms such as FastAPI, React, PostgreSQL, InfluxDB, AWS ECS/Fargate, S3, SharePoint/Graph, or Jira.
Experience with instrument-control methods such as SCPI/TCP, HTTP/XML, SNMP, SSH, or similar interfaces.

Responsibilities

Design and develop automated test frameworks, scripts, APIs, dashboards, and tools using Python.
Develop end-to-end and hardware-in-the-loop (HIL) test suites for satellite, gateway, RF, payload, embedded, and communication-system workflows.
Build and maintain automation with web GUI support, cloud-triggered job execution, instrument drivers, result storage, and automated report generation.
Automate RF and system validation procedures that control lab equipment.
Develop and maintain analytics and monitoring workflows for gateway/satellite platforms.
Build and maintain AI-agent tooling for the automation stack, including MCP servers and APIs that expose lab equipment, telemetry, dashboards, and CI systems as agent-callable tools operating within defined cost, token, and latency budgets.
Analyze test results, identify root causes, debug automation failures, and collaborate with developers and engineering teams to resolve issues.
Present analysis visually in a way that is immediately clear to its audience: dashboards, charts, and reports that surface findings and required actions, readable by engineers and non-specialist stakeholders alike.
Create and maintain detailed automation documentation, test plans, user guides, reports, acceptance criteria, and operational handover material.
Collaborate with cross-functional engineering teams to ensure test coverage, repeatability, maintainability, product quality, and operational reliability.