Business Engineering is looking for impact-driven, entrepreneurial engineers ready to drive projects from ideation to implementation and beyond. We are AI and technology experts that apply our software engineering skills to bring a unique blend of business and technology expertise to ensure our partners succeed. Our team is at the intersection of business and AI innovation where you will operate similarly to a Forward-Deployed Engineer by solving real-world business challenges with game-changing AI technology that impacts businesses and consumers across the world. You will deliver scalable production-grade code across Meta's platforms in collaboration with other product engineering teams. You will get to learn and build on different tech stacks and languages in a rapidly moving, zero-to-one AI domain alongside industry-leading businesses. The work we do exceeds the boundaries of what is possible quickly, and at scale. This role lets you apply your passion for customers, engineering, and problem-solving to delivering real-world results at Meta scale. Our Business Engineering team is at the forefront of the AI frontier - and we're just getting started.
Responsibilities
Contribute to building next-gen AI products and improve existing ones in collaboration with Meta product engineering teams and cross functional partners to meet business needs Understand business challenges to define and drive strategies to help businesses grow at scale Design and build end-to-end systems, GTM automation, and launch-plan strategies Use broad range of technical and soft skills to build productive relationships with our partners, and independently resolve complex technical and business needs Guide workflow changes, and gain consensus from stakeholders while driving toward solutions Respond and maintain effective communication with industry partners and internal stakeholders Build and manage working relationships with technical counterparts; Mentor and share knowledge with peers, creating positive atmosphere amongst team Conduct code reviews and provide constructive feedback while quickly actioning feedback from code reviews conducted of your code Influence decision-making through presentation of data-centric business topics Serve as a subject matter expert within Business Engineering and provide consultation on domain-level projects Participate in interviewing and onboarding of new team members
Qualifications
Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience Currently has, or is in the process of obtaining a Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience 5+ years of experience as a software engineer building and shipping production quality code in dynamic, ambiguous environments Experience with designing, building, and iterating on scalable software platforms applications and taking products from zero-to-one to a level of maturity Experience working with LLMs, agentic AI, and/or related AI/ML technologies Experience working in highly collaborative, dynamic, and ambiguous environments Experience with open source languages such as PHP, Python, Java, or JavaScript Frameworks Experience communicating technical concepts to non-technical audiences Experience with shipping reliable, scalable, and efficient code, with an emphasis on long-term maintainability, in partnership with all appropriate reviewers, in manageable pieces with relevant documentation and test plans Willingness to travel up to 20% of the time Fluency in English is required Experience working in a startup or similar early stage company Knowledge of the AI, advertising, and social media landscape globally Experience working with enterprise customers and B2B GTM motion Experience with agile software development methodologies Experience working with global teams 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) Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies