Meta recently launched its Business Agent, helping businesses of every size use AI to boost productivity and deliver more personalized customer experiences. Business Support Engineering will be at the forefront of this shift, and we’re looking for an engineer to play a pivotal role supporting Meta’s partners bringing demonstrated experience in distributed systems and API troubleshooting and a focus on improving the end-to-end support experience. As a Business Support Engineer, you will work closely with cross-functional teams and business partners across the globe, incorporating AI-driven business solutions into their service offerings. You will track industry advancements and partner experiences, evaluating their impact and influencing the product's strategic roadmap.
Responsibilities
Architect global troubleshooting methodologies and escalation frameworks to enhance Team operational excellence and engineering standards Co-Lead the Team AI-native technical strategy, driving large-scale adoption of AI tools to transform support workflows and value delivery Build, launch, and optimize complex AI architectures using Llama and other LLMs, owning the full lifecycle from prototype to production Develop performance monitoring systems for partner integrations to ensure high availability; leverage metrics to proactively identify issues and drive improvements across teams Provide 24/7 oncall support coverage via rotation schedule (including weekends) Partner with Internal and Cross functional leadership to identify systemic support issues and influence roadmaps with data-driven proposals to eliminate root causes Set technical communication standards, authoring reference architectures and representing the team internally and externally Manage complex, cross-functional programs while fostering continuous AI/ML learning across the team Lead zero-to-one initiatives, anticipating future platform and partner needs in advance
Qualifications
Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience 8+ years experience as a software engineer building and shipping production quality code Software engineering or Site Reliability Engineering background Proven experience in API development on cloud-based infrastructures, being able to debug, identify root causes and resolve independently outages impacting Meta Partners Experience with the full web stack, REST API, Python, PHP/Hack, JavaScript/React development along with debugging and bug management support Knowledge of fine-tuning and optimization of PyTorch models and at least one LLM such as LLaMA, GPT, Claude, Falcon, etc Experience in communicating with technical and business audiences and writing technical documentation Experience in assessing, analyzing, and resolving operational issues using data analysis (SQL) Experience building and deploying solutions on cloud platforms (e.g., AWS, GCP, Azure) Success in cross-cultural engineering environments with international stakeholders Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews) Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews) Hands-on experience working with large language models and AI agents Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements) Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements) Experience with data transformation, model selection/training/optimization, and deployment at scale Experience in partner-facing or customer-centric engineering roles Experience with Open Source cloud stacks like Kubernetes, Kubeflow, Docker containers