Software Engineer (Technical Leadership) - AI Solutions and Automation + Support

Meta•Bellevue, WA

11d•$219,000 - $301,000

About The Position

Meta is hiring an experienced engineer for its AI Solutions and Automation + Support (ASA+S) organization. The team applies AI and autonomous agents to products and support experiences used by billions of people, building agents that address real problems for users, creators, and businesses, as well as platforms, evaluation systems, and model infrastructure that enable safe, scalable deployment. The work spans applied AI research and production, including developing and optimizing LLM and agentic systems, creating trustworthy data and evaluation foundations, and taking new techniques from prototype to production. The role focuses on emerging agent problems and delivering solutions to real users. The engineer will shape the team's goals, technical direction, and long-term roadmap for AI solutions and large cross-company efforts. They will identify opportunities for LLM-based automation, gather partner requirements, and guide product enablement, autonomous agent solutions, and AI quality improvements. The role also involves communicating complex AI systems and their impact, tracking emerging AI techniques, mentoring researchers and engineers, and driving delivery of high-quality, scalable, cost-efficient AI/ML systems.

Requirements

Bachelor's degree in Computer Science, Computer Engineering, or a relevant technical field, or equivalent practical experience.
12+ years of programming experience in a relevant language, or 8+ years of programming experience in a relevant language with a PhD.
Experience influencing and advising executive stakeholders across organizations.
Experience using data and analysis to explain technical problems and provide detailed feedback and solutions.
Experience collaborating with cross-functional partners, such as product, design, and data science, to define requirements and deliver integrated solutions.
Proven track record of planning multi-year roadmaps in which short-term projects advance a long-term mission.
Experience driving large cross-functional engineering efforts across multiple teams or organizations.

Nice To Haves

Knowledge of NLP techniques, including text preprocessing, tokenization, and sentiment analysis.
Ongoing AI skill development, such as prompt/context engineering and agent orchestration, and staying current with emerging AI technologies.
Understanding of information retrieval concepts, such as indexing, querying, and ranking.
Experience implementing responsible and ethical AI practices, such as risk assessment, bias mitigation, and quality and accuracy reviews.
Experience with data structures and algorithms, including graph theory and optimization techniques.
Track record of designing and implementing agentive AI systems and frameworks, such as agent harnesses and multi-agent orchestration, in production.
Master's degree or PhD in Computer Science or a related technical field.
Experience with frameworks such as TensorFlow, PyTorch, or Scikit-learn.
Ability to integrate AI tools to optimize or redesign workflows and drive measurable impact, such as efficiency gains or quality improvements.
Experience building large-scale, multi-stage reasoning systems in high-QPS production environments, including LLM post-training such as reinforcement learning or fine-tuning to improve quality and cost.

Responsibilities

Define and drive the team's goals and technical direction for AI Solutions, delivering measurable business impact for priority product verticals and improving organizational efficiency through LLM-based automation.
Communicate complex AI systems, including LLM post-training, multimodal content understanding, agent harnesses, and agentic platforms, and explain their impact to engineers, partners, and leadership.
Track industry and company-wide AI trends, assess and develop new techniques, and foster innovation, rapid prototyping, and technical rigor.
Partner with organizations and cross-functional leaders, mentor applied researchers and engineers, and raise team and organizational performance while ensuring end-to-end delivery of high-quality, scalable AI/ML systems.
Work as an AI-native engineer by using AI agents and tools in daily design, development, and delivery, and expand these practices across the team.
Identify high-leverage opportunities for LLM-based automation across Meta's product portfolio and influence cross-functional partners on staffing and prioritization.
Lead the long-term technical vision and roadmap for large, cross-company AI efforts aligned with the mission of delivering cost-efficient, performant AI models.
Gather and synthesize partner-team requirements into a roadmap for AI solutions, including rapid product integration, autonomous agent problem-solving, and scaling AI quality for complex problems.
Identify and resolve performance, cost, and scalability issues in AI systems and lead efforts to reduce technical debt.