Software Developer, Scaled Ops AI Acceleration Team
Meta · Austin
About the role
Build and deploy AI-powered automation for operational processes as part of a small team, doing full-stack development. Guide contractor developers and report impact.
Read the full posting text
From Meta's job posting, shown as published. Last checked Oct 29, 2026.
Meta is seeking experienced Software Developer to join the Scaled Operations AI Accelerator Team. This small team is responsible for rapidly designing, developing, and deploying AI-powered automation solutions that transform operational processes and drive efficiency at scale. As a Software Developer, you will play a pivotal role in building and implementing innovative solutions using AI technologies, collaborating across functions, and managing the work of contractor and/or vendor workers to deliver measurable impact across Scaled Operations.
Responsibilities
Full stack development. Design, develop, deploy, and maintain AI-powered automation solutions to optimize and automate key operational processes Rapidly prototype, iterate, and implement technical solutions that drive full-time employee efficiency using AI technologies Collaborate with process owners, architects, product managers, and cross-functional teams to identify high-impact automation opportunities and deliver solutions aligned with business needs Apply full-stack engineering skills, including backend, frontend, and data engineering, to build robust, scalable, and maintainable systems Manage and guide contractor workers and/or vendor workers in the development and delivery of technical solutions, ensuring quality, compliance, and alignment with team objectives Ensure all solutions adhere to Meta’s security, privacy, and compliance requirements Communicate technical concepts, project status, and solution impact clearly to both technical and non-technical audiences Stay current with advancements in AI/ML and automation, and experiment with new tools and approaches to foster innovation and continuous improvement Contribute to the development of playbooks, reusable templates, and best practices to scale successful automations across Scaled Operations Track, analyze, and report on key metrics and business impact of automation initiatives
Qualifications
8+ years of experience in software engineering, support engineering, reliability engineering or related 6+ years of experience in one or more of the following areas: machine learning, recommendation systems, natural language processing, data mining, artificial intelligence, AI-Infrastructure, or related technical field Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience Bachelor’s degree in Computer Science, Computer Engineering, related technical field, or equivalent experience Experience with the full web stack, REST API, Python, PHP/Hack, JavaScript/React development along with debugging and bug management support Knowledge on fine-tuning and optimizations of PyTorch models and with at least one LLM such as Llama, GPT, Claude, Falcon, etc Experience in communicating with technical and business audiences and creating technical documentation Experience assessing, analyzing, and resolving operational issues using data analysis (SQL) Experience supporting and guiding contractor workers and/or vendor workers in technical solution delivery Demonstrated collaborate in cross-functional teams and deliver results in a demanding environment Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews) Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements) Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies Experience with Meta’s internal tools and platforms Familiarity with Global Operations processes and workflows Advanced degree in Computer Science, Engineering, or related field Experience developing playbooks, reusable templates, and best practices for automation at scale that can be leveraged by less technical partners
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