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

Meta; Bellevue (WA); Presencial; USD 180 000 - 280 000; Tempo integral

Resumo da oferta

Meta is seeking highly experienced engineers to join the AI Solutions and Automation + Support (ASA+S) team in Bellevue, WA. You will help build and optimize large-scale AI systems, including LLMs, agents, and evaluation frameworks, delivering production-ready capabilities used across products and services.

You will influence executives, drive multi-year roadmaps, and collaborate across teams to turn frontier AI research into scalable production solutions that impact billions of users.

Qualificações

• Proven track record of planning multi-year roadmaps aligning short-term work with a long-term mission.
• Experience communicating with executives and driving cross-functional solutions.
• Strong background in NLP, data structures, and graph/optimization techniques.
• Experience deploying large-scale, multi-stage reasoning systems in high-QPS production environments.
• Experience with agent architectures and agent orchestration in production.

Conhecimentos

12+ years programming

Executive stakeholder influence

Data-driven problem solving

Cross-functional collaboration

Roadmap planning

Large cross-functional engineering

NLP techniques

AI tool integration

Prompt engineering

Agent orchestration

Reinforcement learning/fine-tuning

Graph theory/optimization

Information retrieval concepts

Formação académica

Masters or PhD in CS or related

Ferramentas

TensorFlow

PyTorch

Scikit-learn

Descrição da oferta de emprego

Meta is seeking experienced engineers to join AI Solutions and Automation + Support (ASA+S), where we apply state-of-the-art AI and autonomous agents to the products and support experiences used by billions of people. We build agents that resolve real problems for users, creators, and businesses, along with the platforms, evaluation systems, and model infrastructure that let those agents ship safely and at scale. This is applied AI where research meets production: you'll build and optimize LLM and agentic systems, design the data and evaluation foundations that make them trustworthy, and take frontier techniques from prototype to production. It's deliberately high-leverage work; what we prove once becomes a platform that other teams build on. If you want to work on genuinely novel agent problems and see your work reach real users quickly, this is the right team for you.

• 12+ years of programming experience in a relevant language OR 8+ years experience with a PhD Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
• Experience influencing and advising executive stakeholders across organizations
• Experience utilizing data and analysis to explain technical problems and provide detailed feedback and solutions
• Experience communicating and working across functions to drive solutions
• Proven track record of planning multi-year roadmaps in which short-term projects ladder to the long-term mission
• Experience driving large cross-functional/industry-wide engineering efforts
• Experience with frameworks like TensorFlow, PyTorch, or Scikit-learn
• Demonstrated experience with data structures and algorithms, including graph theory and optimization techniques
• Knowledge of NLP techniques, including text preprocessing, tokenization, and sentiment analysis
• 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)
• Master's degree or PhD in Computer Science or a related technical field
• Understanding of information retrieval concepts, such as indexing, querying, and ranking
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
• Experience building large-scale, multi-stage reasoning systems in high-QPS production environments, including LLM post-training (e.g., reinforcement learning, fine-tuning) to improve quality and cost
• Track record of designing and implementing agentive AI systems and frameworks (e.g., agent harnesses, multi-agent orchestration) in production