Business Support Engineer - AdTech

We are looking for an engineer to play a key role in providing technical, engineering support to Meta’s Advertising partners, Customers and clients globally. You will have the opportunity to work together with a global team of Business Support Engineers who are expert in Meta’s Adtech to provide proactive and reactive support for partner issues and integrations while partnering with our broad cross functional teams to ensure a high quality for our products and satisfactory experience for our partners and customers. We work directly with Platform and Infrastructure teams to investigate and resolve issues reported by our partners, to properly assess and agree on actions to be taken for necessary fixes and continuous improvements in our products and deployments.

As a Business Support Engineer working on Ads at Meta, you will primarily support on Meta’s Ads Products but also have the opportunity to work cross-functionally in several of our key business areas across Business Messaging, Telecommunications and combine your experience with customer service skills with a product focus to ensure that key insights are communicated to our product teams. We are looking for people who have subject-matter knowledge in managing and maintaining integrations with 3rd-party services, who help foster developer/business relationships, who demonstrate critical thinking & blending systems design with business needs, and who have a desire to improve the support experience of our customers. You will understand industry trends, partner solutions/integrations and their implications for our product roadmap. You will work closely with other regional offices and partnership teams to support a broad range of partners across the globe to integrate Meta’s Business Products into their offering.

Responsibilities

Provide proactive and reactive engineering support for partners, independently managing complex outages to ensure high partner satisfaction Troubleshoot large-scale distributed systems and partner integrations, maintaining reliable systems through thorough debugging, root-cause analysis, and follow-up improvements Leverage AI tools to accelerate troubleshooting, automate repetitive tasks, and scale your impact with an 'AI native' mindset Build, launch, and optimize AI solutions 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 a rotation schedule (including weekends) Collaborate with Platform and Infrastructure teams to investigate issues, align on fixes, and drive continuous product improvement Create clear documentation, specs, guides, and presentations to communicate complex AI concepts to diverse audiences, scaling the team's knowledge internally and externally 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 other engineers on technical troubleshooting and project executions Proactively and independently analyze information to identify specific trends/opportunities, recommend appropriate and relevant tactical improvements, anticipate future business needs to improve the overall support experience, and share this knowledge across the team

Qualifications

Bachelor's degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience 5+ years of experience in software engineering or site reliability engineering or support engineering Proven experience in API development on cloud-based infrastructures, with the ability to debug, identify root causes, and independently resolve outages impacting Meta partners Experience with the full web stack, REST APIs, Python, PHP/Hack, and JavaScript/React development, along with debugging and bug management Knowledge of fine-tuning and optimization 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 writing technical documentation Experience in assessing, analyzing, and resolving operational issues using data analysis (SQL) Experience in managing multiple concurrent projects and driving initiatives in a cross-functional environment Professional working proficiency in English is required because this role involves close collaboration with internal stakeholders and external customers whose primary business language is English Experience with Open Source cloud stacks like Kubernetes, Kubeflow, Docker containers Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews) Experience transforming data, model selection/training/optimization, and deployment at scale Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies Hands-on experience working with large language models and AI agents Experience building and deploying solutions on cloud platforms (e.g., AWS, GCP, Azure) Experience working in engineering environments with geographically distributed, cross-cultural teams and international stakeholders Experience in partner-facing or customer-centric engineering roles Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)