Background information about the job or company (e.g., role context, company overview)

The International Rescue Committee is a global humanitarian aid, relief and development nongovernmental organization.

This is a senior technical leadership role for someone who wants to build at the frontier of applied AI in service of humanitarian impact. You will lead a team of engineers and AI specialists designing and shipping AI-powered, program-facing solutions — primarily agentic systems, predictive analytics, and AI diagnostics deployed in low-resource and high-stakes settings.

You will own three things:

Technical strategy and direction for IRC's program-facing AI portfolio. You will help translate IRC's AI ambitions into a clear technical roadmap, make build-vs-buy-vs-partner decisions, and set the architectural direction for systems that need to work reliably in some of the hardest operating environments on earth — including AI that runs offline on low-cost smartphones, agentic systems with high safety standards, and diagnostic models trained on populations the major datasets ignore.

A high-performing engineering team. You will manage and grow a team of engineers, applied AI engineers, and QA specialists; raise the bar on engineering quality; and build the kind of culture that attracts top technical talent to mission-driven work.

Deep partnership with program leaders and strategic partners. You will be a true thought partner to IRC's program experts in health, education, protection, resettlement, and emergency response — co-designing solutions with them rather than receiving requirements. You will also help us get maximum value from our flagship partnerships with Anthropic, OpenAI, and other frontier labs, with direct access to frontier models, early features, and the researchers building them.

Responsibilities or duties

• AI Strategic Leadership
  • Translate IRC's AI strategy and program priorities into a prioritized technical roadmap, in close partnership with program leaders, the SVP for Research, Innovation, AI, and People & Culture, and the T4P demand pipeline.
  • Stay at the edge of AI/ML advances — particularly in agentic systems, multimodal models, and edge/on-device inference — and bring promising approaches to IRC's programs.
  • Serve as a core member of IRC's AI leadership, helping shape organizational direction alongside the SVP for Research, Innovation, AI, and People & Culture and other senior leaders.
  • Champion responsible, human-centered AI deployment in some of the most sensitive humanitarian contexts in the world, with the safety standards those contexts demand.
  • Represent IRC in technical discussions with partners, peer organizations, donors, and the broader humanitarian and AI sectors.
• Team Leadership and Management
  • Manage and develop a team of engineers, applied AI engineers, and QA specialists. Hire well, raise the bar, and build a culture that strong technical people want to be part of.
  • Establish engineering quality standards, development practices, and documentation protocols.
  • Maintain a prioritized backlog of program innovations and manage team capacity against demand.
  • Mature the team's AI development and DevOps practices and grow stakeholder buy-in across the organization.
  • Identify opportunities to secure budget resources in support of innovation priorities.
• Cross-functional Partnership
  • Act as a genuine thought partner to program leaders — bringing AI fluency to their problems and humility about the field realities
  • Co-design solutions that actually work in the field, not technology-first answers in search of problems.
  • Partner with the Enterprise Applications team to ensure smooth handoffs of proven innovations for enterprise-wide scale-up.
  • Coordinate with the Enterprise Applications DevOps team on integration touchpoints, infrastructure dependencies, and shared engineering standards.
• Flagship AI Partnerships
  • Serve as the technical lead on IRC's strategic partnerships with frontier AI organizations — helping turn early relationships into long-term, high-leverage collaborations.
  • Identify where partnership access (compute, frontier models, technical expertise) can unlock outsized program impact.
• Solution Design and Engineering
  • Lead the design and development of AI-driven and program-specific technology solutions, owning the full development lifecycle from requirements through handoff.
  • Interface with program and business stakeholders to gather requirements, define technical solutions, and recommend approaches grounded in a detailed understanding of program goals.
  • Design and oversee high-availability architectures in Microsoft Azure, incorporating appropriate redundancy, security, backup, and recovery strategies — including for sensitive humanitarian data.
  • Research and recommend technology products, services, and standards — particularly in AI/ML — to support procurement, development, and strategic decision-making.
• DevOps and Engineering Operations
  • Oversee deployment pipelines, CI/CD automation, infrastructure-as-code, and QA processes to ensure efficient and reliable software delivery.
  • Ensure ongoing availability and performance of applications through monitoring, scaling, and proactive operations management.
  • Track and optimize cloud and model-inference costs.
  • Maintain technical and policy documentation for all assets under the team's management.

Key Working Relationships

Position Reports to: Chief Information Officer, working in close partnership with the SVP for Research, Innovation, AI, and People & Culture

Position directly supervises: Engineers, applied AI engineers, ML specialists, and QA staff on the T4P Development team.

Other internal contacts: Program leaders across CRRD, RAI, R&I, and Signpost; the Enterprise Applications and DevOps teams; the AI governance and policy team; AI@Scale (I@S) leadership; IT leadership across regions and HQ.

External contacts: Strategic partners with leading AI organizations; technology vendors; AI sector peers; NGO tech community; major foundation funders.

Qualifications or requirements (e.g., education, skills)

Strong candidates will bring most — not necessarily all — of the following:

AI and engineering depth

• Hands-on experience building and shipping production AI systems — agentic frameworks, LLM applications, RAG systems, computer vision, or applied ML pipelines.
• Solid full-stack foundation (Python, JavaScript/TypeScript, and modern frameworks) with the technical credibility to engage directly with engineers on architecture and design decisions.
• Experience with cloud architecture (Azure preferred; AWS/GCP transferable), including AI services, DevOps pipelines, and cost-effective scaling.
• Working knowledge of data security and privacy practices for sensitive or personally identifiable information.

Leadership and collaboration

• Ability to engage non-technical leaders as a peer: explaining trade-offs clearly, listening well, and translating between worlds.
• Comfort operating across global teams, time zones, and contexts very different from your own.

Mindset

• Genuinely motivated by humanitarian impact
• Leads with humility. Deep respect for the people closest to the problem, including those without technical backgrounds.
• Technically curious and forward-looking — reads, experiments, and brings new ideas to the team.

Nice to have

• Experience deploying AI in low-resource, low-bandwidth, or offline contexts.
• Prior work with humanitarian, development, or global health organizations.
• French or Arabic language skills.

• AI Strategic Leadership
  • Translate IRC's AI strategy and program priorities into a prioritized technical roadmap, in close partnership with program leaders, the SVP for Research, Innovation, AI, and People & Culture, and the T4P demand pipeline.
  • Stay at the edge of AI/ML advances — particularly in agentic systems, multimodal models, and edge/on-device inference — and bring promising approaches to IRC's programs.
  • Serve as a core member of IRC's AI leadership, helping shape organizational direction alongside the SVP for Research, Innovation, AI, and People & Culture and other senior leaders.
  • Champion responsible, human-centered AI deployment in some of the most sensitive humanitarian contexts in the world, with the safety standards those contexts demand.
  • Represent IRC in technical discussions with partners, peer organizations, donors, and the broader humanitarian and AI sectors.
• Team Leadership and Management
  • Manage and develop a team of engineers, applied AI engineers, and QA specialists. Hire well, raise the bar, and build a culture that strong technical people want to be part of.
  • Establish engineering quality standards, development practices, and documentation protocols.
  • Maintain a prioritized backlog of program innovations and manage team capacity against demand.
  • Mature the team's AI development and DevOps practices and grow stakeholder buy-in across the organization.
  • Identify opportunities to secure budget resources in support of innovation priorities.
• Cross-functional Partnership
  • Act as a genuine thought partner to program leaders — bringing AI fluency to their problems and humility about the field realities
  • Co-design solutions that actually work in the field, not technology-first answers in search of problems.
  • Partner with the Enterprise Applications team to ensure smooth handoffs of proven innovations for enterprise-wide scale-up.
  • Coordinate with the Enterprise Applications DevOps team on integration touchpoints, infrastructure dependencies, and shared engineering standards.
• Flagship AI Partnerships
  • Serve as the technical lead on IRC's strategic partnerships with frontier AI organizations — helping turn early relationships into long-term, high-leverage collaborations.
  • Identify where partnership access (compute, frontier models, technical expertise) can unlock outsized program impact.
• Solution Design and Engineering
  • Lead the design and development of AI-driven and program-specific technology solutions, owning the full development lifecycle from requirements through handoff.
  • Interface with program and business stakeholders to gather requirements, define technical solutions, and recommend approaches grounded in a detailed understanding of program goals.
  • Design and oversee high-availability architectures in Microsoft Azure, incorporating appropriate redundancy, security, backup, and recovery strategies — including for sensitive humanitarian data.
  • Research and recommend technology products, services, and standards — particularly in AI/ML — to support procurement, development, and strategic decision-making.
• DevOps and Engineering Operations
  • Oversee deployment pipelines, CI/CD automation, infrastructure-as-code, and QA processes to ensure efficient and reliable software delivery.
  • Ensure ongoing availability and performance of applications through monitoring, scaling, and proactive operations management.
  • Track and optimize cloud and model-inference costs.
  • Maintain technical and policy documentation for all assets under the team's management.

• Hands-on experience building and shipping production AI systems — agentic frameworks, LLM applications, RAG systems, computer vision, or applied ML pipelines.
• Solid full-stack foundation (Python, JavaScript/TypeScript, and modern frameworks) with the technical credibility to engage directly with engineers on architecture and design decisions.
• Experience with cloud architecture (Azure preferred; AWS/GCP transferable), including AI services, DevOps pipelines, and cost-effective scaling.
• Working knowledge of data security and privacy practices for sensitive or personally identifiable information.
• Ability to engage non-technical leaders as a peer: explaining trade-offs clearly, listening well, and translating between worlds.
• Comfort operating across global teams, time zones, and contexts very different from your own.
• Experience deploying AI in low-resource, low-bandwidth, or offline contexts.
• French or Arabic language skills.

• 7–10+ years in software engineering or technical product development, with 3+ years leading engineers as a manager or tech lead.
• A track record of building or growing strong engineering teams — hiring, raising the bar, and creating a culture people want to be part of.
• Experience deploying AI in low-resource, low-bandwidth, or offline contexts.
• Prior work with humanitarian, development, or global health organizations.