Business Support Engineer

**Summary:** 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. **Required Skills:** Business Support Engineer Responsibilities: 1. Provide proactive and reactive engineering support for partners, independently managing complex outages to ensure high partner satisfaction 2. Troubleshoot large-scale distributed systems and partner integrations, championing operational excellence and engineering craftsmanship 3. Leverage AI tools to accelerate troubleshooting, automate repetitive tasks, and scale your impact with an 'AI native' mindset 4. Build, launch, and optimize AI solutions using Llama and other LLMs, owning the full lifecycle from prototype to production 5. Develop performance monitoring systems for partner integrations to ensure high availability 6. leverage metrics to proactively identify issues and drive improvements across teams 7. Provide 24/7 oncall support coverage via rotation schedule (including weekends) 8. Collaborate with Platform and Infrastructure teams to investigate issues, align on fixes, and drive continuous product improvement 9. Create clear documentation, specs, guides, and presentations to communicate complex AI concepts to diverse audiences, scaling the team's knowledge internally and externally 10. Drive end-to-end execution, using sound judgment to manage stakeholder expectations and ensuring clear alignment. Develop and share AI/ML expertise, actively coach and mentor peers on technical troubleshooting and project execution **Minimum Qualifications:** Minimum Qualifications: 11. Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience 12. 5+ years of experience in Software Engineering or Site Reliability Engineering 13. Proven experience in API development on cloud-based infrastructures, with the ability to debug, identify root causes, and independently resolve outages impacting Meta partners 14. Experience with the full web stack, REST APIs, Python, PHP/Hack, and JavaScript/React development, along with debugging and bug management 15. Knowledge on fine-tuning and optimizations of PyTorch models and with at least one LLM such as LLaMA, GPT, Claude, Falcon, etc 16. Experience in communicating with technical and business audiences and writing technical documentation 17. Experience in assessing, analyzing, and resolving operational issues using data analysis (SQL) **Preferred Qualifications:** Preferred Qualifications: 18. Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews) 19. Experience working in engineering environments with geographically distributed, cross-cultural teams and international stakeholders 20. Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies 21. Experience in partner-facing or customer-centric engineering roles 22. Hands-on experience working with large language models and AI agents 23. Experience transforming data, model selection/training/optimization, and deployment at scale 24. Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements) 25. Experience with Open Source cloud stacks like Kubernetes, Kubeflow, Docker containers 26. Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews) 27. Experience building and deploying solutions on cloud platforms (e.g., AWS, GCP, Azure) 28. Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies 29. Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements) **Public Compensation:** $142,000/year to $201,000/year + bonus + equity + benefits **Industry:** Internet **Equal Opportunity:** Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment. Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at accommodations-ext@meta.com.