Senior AI Engineer

Bill & Melinda Gates Foundation•Seattle, WA

3d•$173,100 - $259,700•Hybrid

About The Position

Within Business Operations and the IT organization, the Enterprise Data Solutions (EDS) team designs and delivers enterprise-scale platforms and services across Knowledge Management, Artificial Intelligence (AI), Data Engineering, Business Intelligence, Data Infrastructure, and Health Data Platforms. The EDS team’s mission is to empower the Foundation with reliable, innovative, and data-driven solutions that enable timely, informed decision-making and support critical operational workflows. Central to this mission is the development of an AI-powered intelligent data and AI platform that enables employees to discover and interact with connected knowledge through conversational experiences. The Knowledge Mgmt & Insights (KMI) is an AI-first team and leverages technologies such as large language models (LLMs), knowledge graphs, and modern data platforms to deliver scalable, impactful enterprise-wide AI solutions. This position is a limited-term position for 24 months and located in our Seattle, Washington office. This is a hybrid role with a requirement of 50% in office. As a Senior AI Engineer, you are a highly skilled individual contributor responsible for designing, building, and deploying AI solutions that support foundation and affiliate staff around the world. You bring strong technical expertise and a hands-on approach to developing scalable, secure, and reliable AI systems that address real organizational needs. You translate defined problem statements into effective technical solutions, partnering closely with the team and contributing directly to implementation and delivery. In this role, you play a key part in executing AI initiatives—designing solutions, integrating systems, and ensuring solutions are production-ready and aligned with engineering best practices. You collaborate with Lead Engineers and cross-functional partners to deliver high-impact AI capabilities, while proactively identifying opportunities to improve performance, usability, and scalability. You contribute to code quality, documentation, and shared standards, helping strengthen the team’s engineering discipline. You also support other engineers through knowledge sharing and collaboration, while continuing to grow your own expertise in AI technologies and approaches. Your work enables innovative access to knowledge assets at the foundation, helping drive better decision-making and streamline workflows to advance the organization’s mission globally.

Requirements

Bachelor’s degree or equivalent experience; typically requires an advanced degree or equivalent experience and a minimum of 8 years of prior relevant experience.
Strong analytical and problem-solving abilities, with a commitment to operational excellence, continuous learning, and raising the bar on engineering practices
Strong programming skills in Python
Hands-on experience with Claude Code, GitHub Copilot, Codex or other AI-assisted coding tools
Hands-on experience with state-of-the-art LLMs, agentic systems, and RAG architecture, graph technologies and practical knowledge of embeddings, tokenization, evaluation, observability, and frameworks such as LangChain and LlamaIndex.
Experience deploying, monitoring, and maintaining ML/LLM systems in production.
Deep understanding of data privacy, security, and compliance considerations when building AI-powered systems.
Excellent communication and influencing skills, with the ability to engage immediate and extended team, build consensus, and move work forward in ambiguous or rapidly evolving environments.
3+ years of professional experience with cloud technologies preferably Azure
Proven ability to prototype, iterate, and productionize innovative AI solutions that deliver measurable business value.
Knowledge of ethics in AI and responsible AI development.
Experience with agile development methodologies such as Scrum or Kanban
Ability to travel as needed.
Ability to participate in on-call duties
Must be able to work effectively across geographic and cultural boundaries.
Commitment to the foundation’s mission and values, including diversity, equity, and inclusion.
Must be able to legally work in the country where this position is located without visa sponsorship. The Foundation does not provide immigration-related sponsorship for this role. This includes direct company sponsorship and any work authorization requiring a written submission or other immigration support from the company (eg: H-1B, O-1, L-1, E, OPT, STEM-OPT, CPT, TN, J-1, etc.).

Responsibilities

Develop and implement agentic AI systems, including multi-step workflows, tool use, and autonomous task orchestration using LLM-based frameworks
Design, build, and deploy scalable AI/ML solutions using Python and cloud-native services in Microsoft Azure (e.g., Azure OpenAI, Azure Foundry, Azure AI Search)
Integrate AI capabilities into enterprise applications and workflows through APIs, microservices, and Azure-based architecture
Translate business and technical requirements into robust, production-ready solutions, balancing performance, scalability, and maintainability
Collaborate with engineers, product managers, and stakeholders to deliver AI solutions aligned to requirements
Contribute to solution design and architecture discussions, including tooling and implementation trade-offs
Use AI-assisted development tools (e.g., Claude Code, Codex, GitHub Copilot) to improve development efficiency while maintaining strong code quality
Contribute to code reviews, automated testing, and CI/CD pipelines to ensure reliable and secure deployments
Deploy, monitor, and optimize AI solutions in Azure, addressing performance, cost and reliability
Troubleshoot and resolve issues across development and production environments
Contribute to reusable components, shared frameworks and engineering standards for AI development across the team
Support data preparation, prompt engineering, and evaluation processes to improve model performance and outcomes
Stay current with emerging AI technologies and proactively identify opportunities to apply them to enhance solutions where relevant