Requirements

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

• 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.
  
• 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.