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Responsibilities
- Architect and own global troubleshooting methodologies, escalation frameworks, and engineering standards that elevate the operational excellence of the Business Support Engineering organization
- Lead the team's AI-native technical strategy, driving large-scale adoption of AI and LLM-based tools to transform partner support workflows and accelerate issue resolution
- Design, build, and optimize complex AI architectures using large language models, owning the full lifecycle from prototype to production deployment for support automation use cases
- Define and implement performance monitoring systems for partner integrations across Meta's Ads and Business Messaging platforms, leveraging metrics to proactively surface and resolve systemic issues
- Partner with cross-functional leadership across Product, Infrastructure, and Partnership teams to identify root causes of recurring partner issues and influence product roadmaps with data-driven proposals
- Establish technical communication standards for the team, including authoring reference architectures, integration guides, and representing the engineering organization in partner-facing and internal executive forums
- Lead zero-to-one initiatives that anticipate future platform needs, designing scalable support infrastructure for new Meta business product launches and partner integration patterns
- Provide oncall support coverage via rotation schedule to ensure high availability and rapid response for partner-impacting incidents across global time zones
- Mentor and develop other engineers on the team, setting technical direction and fostering an environment of continuous learning in AI, ML, and AdTech domains
- Manage complex, cross-functional programs spanning multiple business areas, driving alignment across regional offices and partnership teams to deliver consistent partner experiences globally
Minimum Qualifications
- Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
- 8+ years of experience as a software engineer or site reliability engineer
- Proven experience in API development on cloud-based infrastructures, being able to debug, identify root causes and resolve independently any outages that are impacting Meta Partners
- Experience with the full web stack, REST APIs, Python, PHP, and JavaScript/React development, along with debugging and bug management
- Experience working with large language models or AI-based tooling in a production or applied context
- Experience communicating with technical and business audiences and writing technical documentation
- Experience in assessing, analyzing, and resolving operational issues using data analysis (SQL)
Preferred Qualifications
- Experience in AdTech platforms, advertising APIs, or business messaging integrations, with familiarity in Meta's Ads or Business Products ecosystem
- Experience fine-tuning, optimizing, and deploying PyTorch-based models or LLM-powered agents at production scale
- Experience with open-source cloud infrastructure tooling such as Kubernetes, Docker, or Kubeflow in a partner integration or support engineering context
- Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
- Demonstrated track record of integrating AI tools to redesign support workflows and deliver measurable efficiency or quality improvements at an organizational level
- Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
- Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
$171,000/year to $240,000/year + bonus + equity + benefits
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