The Airbel Impact Lab is the IRC’s “R&D” unit, working to maximize the impact of every humanitarian aid dollar through rigorous testing, innovative new solutions, and evidence-based scaling. We have led the field in impact measurement and cost analysis, and we drive breakthrough innovations that achieve 10x scale potential, 2x greater impact, and 20% more cost-effectiveness than existing solutions. Our Strategy & Delivery team enables this work by building and delivering the systems, processes, and other infrastructure that help ensure the department is efficient, high-performing, and high-impact. 

Job Overview:  

We are hiring an AI Adoption Lead to transform how Airbel works by embedding AI into the department’s day-to-day operations. This is not a technology-for-technology’s-sake role: it is about understanding how work actually gets done, determining which tasks AI should own versus humans, and reconstructing workflows accordingly. The AI Workflow Lead will work alongside Airbel’s pillar and support teams as a standing resource — diagnosing workflows, co-designing AI-enabled solutions, and building the local capacity teams need to sustain adoption independently. This is an individual contributor role for someone who can use AI platforms to rapidly build functional tools, automations, and workflows without writing traditional code.  

This role sits within the Strategy & Delivery team but operates in close partnership with teams across the department. Rather than deep, sequential embedding with one team at a time, this person will support multiple teams simultaneously — providing hands-on guidance, building reusable tools and templates, and cultivating AI superusers who become self-sustaining champions within their own teams. The goal is not to build a portfolio of AI-enabled products and capabilities that raise the floor of AI fluency across Airbel, not to create dependency on a central AI expert. The AI Adoption Lead will also help establish a lightweight intake and prioritization process for AI work across the department, ensuring the highest-value opportunities are addressed first and that quality expectations are clear. 

The work is concrete and varied. You might spend one week helping a research team redesign how they synthesize literature using AI, another building a prompt library for a team that produces grant proposals, and another coaching a program team through automating their reporting pipeline. Beyond team-level work, you will build and maintain the repeatable infrastructure — playbooks, prompt libraries, workflow documentation — that allows AI-enabled practices to scale across the department. You will also feed learning, best practices, and emerging capabilities into IRC’s broader AI Transformation efforts. 

The ideal candidate is deeply fluent in frontier AI platforms and stays current with rapidly evolving capabilities. They are equal parts analyst, builder, and coach: able to decompose complex workflows, prototype AI-enabled solutions quickly, and bring colleagues along with patience and pragmatism. They have a bias for action, a high bar for what “good” looks like, and the judgment to know when AI adds genuine value versus when it doesn’t. If this person is great at their job, Airbel will be materially faster, sharper, and more capable — not because of any single tool, but because every team will work differently. 

Major Responsibilities: 

Capacity Building & Adoption 

• Provide hands-on coaching, training, and feedback loops that build staff comfort and competence with AI tools. 

• Support teams in developing sophisticated, multi-step prompting workflows against real operational data. 

• Monitor adoption and usage patterns, adjusting approach to ensure sustained uptake rather than one-off experiments. 

• Identify and develop AI superusers within each team who can champion and sustain AI-enabled practices after direct engagement ends. 

Workflow Diagnosis & AI Solution Design 

• Work alongside pillar teams to map and diagnose existing workflows, identifying high-value opportunities for AI-enabled improvement. 

• Build and scale reusable AI-enabled solutions (e.g., prompt libraries, tools, and workflow templates) that can be deployed across teams 

• Prototype and iterate quickly, moving from diagnosis to working solution with minimal overhead. 

• Ensure solutions are practical, sustainable, and designed for handoff (not dependent on ongoing central support).  

Quality Assurance & Responsible AI Use 

• Establish and maintain quality standards for AI-generated content and outputs across the department, ensuring accuracy, consistency, and alignment with Airbel’s mission. 

• Develop review protocols and guardrails that help teams use AI confidently while managing risks around hallucination, bias, and data sensitivity. 

• Contribute to organizational thinking about responsible AI use, ensuring Airbel’s practices reflect both ambition and rigor. 

AI Systems, Intake & Scalable Infrastructure

• Build and maintain repeatable playbooks, prompt libraries, and workflow templates that allow AI-enabled practices to scale across the department. 

• Establish and run a lightweight intake and prioritization process for AI work across the department (e.g., request intake, triage criteria, and a clear queue/roadmap) so effort is driven by impact rather than volume or urgency of requests. 

• Define “what good looks like” for AI-enabled solutions (e.g., quality checks, human review expectations, evaluation approaches, and documentation requirements) and ensure new solutions meet these standards before broad rollout. 

• Document lessons learned, edge cases, and best practices in accessible formats that enable self-service adoption. 

• Continuously update resources as AI capabilities evolve, ensuring the department’s toolkit reflects what’s currently possible. 

Organizational Learning & AI Transformation 

• Feed insights, best practices, and emerging AI capabilities from departmental work into IRC’s broader AI Transformation efforts as directed by the Director of Strategy & Delivery. 

• Stay current with frontier AI developments and continuously reassess what’s possible, proactively identifying new opportunities for the department. 

Job Requirements:

• 4–7 years of relevant professional experience (e.g., process improvement, product management, solutions engineering, research operations, or a related field), with increasing recent focus on applying AI tools to personal and/or team workflows 

• Deep fluency with frontier AI platforms (e.g., Claude’s full suite of tools and capabilities), including comfort executing sophisticated, multi-step prompting against real operational data / context and using AI to generate and iterate on functional tools (e.g., dashboards, automations, lightweight applications) 

• Demonstrated ability to decompose how work actually gets done, determine which tasks AI should own versus humans, and reconstruct workflows accordingly. 

• Strong facilitation skills, with the ability to bring non-technical colleagues along and build their confidence with AI tools. 

• Strong written communication skills, particularly the ability to create clear, usable documentation and instructional materials. 

• Strongly preferred: Experience working across cultures; demonstrated interest in IRC's humanitarian mission strongly preferred.

Application Requirements:

Along with your resume and cover letter, please submit two examples of AI tools, workflows, or applications you have personally built in the past 6 months. This could include: 

• Links to custom GPTs you have created 

• Screenshots or documentation of automation workflows you have built 

• Demos or code samples of agents you have configured 

• Brief descriptions of AI implementations you have led, including the tools used and outcomes achieved 

We are specifically looking for evidence of recent hands-on building experience with current AI tools and platforms. The goal is to see how you approach solving problems with AI, not to evaluate you on years of experience in a field where many of these tools have only existed for months. 

Working Environment: Hybrid or fully in-office are both options.

Compensation: (US: $94,000 - $110,000).Ranges are based on various factors including the labor market, job type, internal equity, and budget.  Exact offers are calibrated by work location, individual candidate experience and skills relative to the defined job requirements.