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About This Role
22 Jul 2026
5 Aug 2026 \- 23:59 UTC
Worldwide
Business Transformation
Permanent
Full\-time
Save the Children International has an exciting opportunity for a Senior Lead, AI, Digital and Data Capacity Development to join our global team.
Team and Role Purpose
Across all sectors, AI, Data and Digital are critical enablers that help organisations deliver better quality work, based on sound decision making and driving efficiency. This is as important if not more critical in the development sector where every $ counts towards supporting the needs of children. There are many systems and tools across the organisation that are used to generate, store and communicate data and information as well as pockets of capabilities and process that is focused on driving continuous improvement. Alongside this and based on this rich data landscape, Digital Programming or ICT4D (information and communication technology for development) is the application of technology for the delivery of programmes for children. Technology can range from bespoke for a specific purpose, or a standard off the shelf digital tool or application. It may be deployed in the field as part of a program delivery (front office) or form part of the program development cycle (back office). Similarly, it could also focus on an enabling technology required to allow further digital developments e.g. connectivity, infrastructure changes etc. Bringing these together and maximising benefit from evolving AI technologies to support programme delivery, data and analytics, operational delivery etc. in a single unit, drives quality delivery and ensures a fully joined up approach.
To ensure we focus our resource and capabilities in the best way to maximise value, a fit for purpose strategy based on our overarching global strategy is key, enabling us to accelerate on priority areas and balance scale with local needs.
Role purpose
A key component of AI, Digital, and Data is ensuring all our people are able to maximise value from these tools in their ongoing work. This will be achieved through a focus on capacity strengthening through formal and informal channels, led by the AI, Data and Digital team. Central to this role is driving a clear vision for the broad adoption of AI across general productivity — setting the strategic direction and governance framework for how the organisation identifies high\-value general productivity approaches and selects the Digital and AI solutions that accelerate its work, and securing the cross\-functional engagement needed to deliver them at scale. As part of this, the role holder will lead global engagement across SCI functions and country leadership to drive adoption of AI across those teams, chairing senior leadership forums and holding SLT, ELT, and Country Director\-level staff accountable for their teams’ use of Digital, Data, and AI. At a Save the Children movement level, the role holder will hold accountability for convening and chairing key cross\-entity forums that build alignment and collaboration on the use of Digital, Data, and AI, bringing together leaders from \~15 member entities and driving consensus on joint, movement\-wide decisions.
To enhance the use of data and AI in making decisions, building capacity of staff to analyse data, use analytical tools, and apply AI effectively will be essential to our culture change. This role will drive that capacity\-building, oversee the development and rollout of AI training and culture change initiatives, embed organisation\-wide standards for the responsible and ethical use of AI, and help shape the strategy for the business intelligence tools and processes that serve end users across the organisation.
- Job Title: Senior Lead, AI, Digital and Data Capacity Development
- Reports To: Director, AI, Data and Digital
- Work Pattern: Hybrid/Remote with flexible working options available
- Location: Any approved Save the Children International office location. For a full list of locations that Save the Children International can hire in, please visit: SCI Careers
- Required Time Zone: Any
- Contract Length: Permanent
- Right to Work: The successful candidate must have the right to work in the country where the role is based, for the duration of employment.
- Language Requirements: English
- International Travel: up to 20%
- Number of people managed in total: Dotted line management of 5 staff seconded from other functions; Manager of a team: Yes; Team Manager (manager of multiple teams): No
- Budget Responsibility: Manages AI training spend as part of AI/Digital/Data budget
- Remit: Global
Principal Accountabilities
- Set strategic direction for how Save the Children will capture value through driving use of AI, Digital, and Data cross\-functionally. As a key part of this, drive and oversee execution of the vision for AI in General Productivity across the organisation.
- Own the multi\-year strategy, roadmap, and prioritisation for Digital, Data, and AI general capability development across Save the Children, making the trade\-off and resource\-allocation decisions required to maximise organisational value.
- Lead the development and implementation of data, analytics, and AI training programmes to enhance organisational capacity, overseeing the design and rollout of initiatives that build AI fluency and drive culture change across the organisation, ensuring all initiatives align with SCI's commitment to diversity, equity, and inclusion
- Drive key communities, including SCA AI Forum and the SCI AI Ethics \& Risk Working Group. Foster an environment that promotes collaboration, knowledge sharing, and mutual learning among all participants
- Drive uptake of organisational policies related to data, analytics, and AI — including guidelines for the responsible and ethical use of AI — ensuring they reflect SCI's values of ambition, accountability, and integrity
- Support engagement with users to gather insights and represent their needs in the design and development of cross\-functional data products and tools, ensuring inclusivity and accessibility
- Oversee the evaluation and continuous improvement of training and capacity\-building efforts, ensuring they meet the evolving needs of the organisation and its diverse members
- Build and steward senior\-level relationships and strategic partnerships with internal and external stakeholders to drive strategic initiatives and advocate for the importance of data, analytics, and AI in achieving SCI's mission
- Act as the organisation's senior accountable lead for AI capability, accountable to the Executive Leadership Team for the delivery and measurable impact of the enterprise\-wide AI adoption strategy
- Represent Save the Children externally as a senior spokesperson and thought leader on the responsible adoption of AI in the international development sector
Experience and Skills
Essential
- Senior leadership and strategic planning: Proven experience setting and owning organisation\-wide strategy at a senior leadership level, with accountability for delivery across multiple functions and geographies
- Senior stakeholder influencing: Demonstrated ability to influence and secure commitment from executive\-level (ELT/SLT) and Country Director\-level leaders across a global, federated organisation
- Setting a vision: Ability to set ambitious and strategic goals for data and analytics training initiatives, ensuring alignment with the organisation's values and mission.
- Change Management: Proficient in driving organisational change and fostering an environment receptive to continuous improvement
- Data Proficiency: Knowledge of data analysis, visualisation, and interpretation techniques to drive evidence\-based decision\-making.
- Analytics Tools Expertise: Familiarity with various data analytics tools and platforms (e.g., SQL, Python, R, Tableau, Power BI)
- User\-Centric Design: Proficient in gathering and incorporating user insights to design inclusive and accessible data products and tools
- Stakeholder Engagement: Proven track record of effectively identifying and engaging key stakeholders, maintaining strong relationships with both internal and external stakeholders to advance strategic initiatives
Desirable
- Non\-profit sector knowledge/experience (especially international development projects)
- Second language – French, Spanish or Arabic
Education and Qualifications
Essential
- Bachelor’s or Master’s degree or equivalent work experience.
Working at Save the Children International
Save the Children is the world's leading organisation for children, employing \~25,000 staff. We save children's lives. We fight for their rights. We help them fulfil their potential. Through our work in 116 countries, we put the most deprived and marginalised children first.
We know that great people make a great organisation, and that our employees play a crucial role in helping us achieve our ambitions for children. We value our people and offer a meaningful and rewarding career, along with a collaborative and inclusive environment where ambition, creativity, and integrity are highly valued.
The work here is challenging but is also immensely rewarding. At Save the Children, you will be in good company, working with talented, like\-minded individuals who are determined to ensure that all children survive, learn, and are protected. Your contribution will help ensure children's voices are heard at the highest levels, and that we achieve our global strategy, Ambition for Children 2030, and reach every last child.
Diversity, Equity and Inclusion and Equal Opportunities
DEI is core to our vision, values and global strategy. Save the Children is committed to creating a truly diverse, equitable and inclusive organisation, and one which will support us in our vision to ensure every child attains the right to survival, protection, development, and participation.
We are committed to equal employment opportunities, regardless of gender, sexual orientation, race, colour, ethnic origin, nationality, disability, marital or civil partnership status, gender reassignment, pregnancy and maternity, caring or parental responsibilities, age, or beliefs and religion. We are committed to diversifying our staff to better represent the communities we serve and actively welcome underrepresented groups to apply.
Reasonable adjustments will be made should any candidate invited to interview require this.
Application Information
Please attach a copy of your CV and cover letter with your application. A full copy of the role profile can be found at SCI Careers. It is recommended that you save a copy of the role profile as it will no longer be available after the advert closes.
Applications will be reviewed on a rolling basis and the job advert may be closed earlier than advertised subject to the volume of suitable applicants. Please submit your application at your earliest convenience to avoid disappointment.
Due to the high volume of applications we receive, only shortlisted candidates will be contacted. Candidates who are successfully shortlisted should expect to hear from us within 2 weeks of the advert deadline.
Our Recruitment Process
- Application review by our recruiting team based on your CV and cover letter
- Two\-stage competency\-based interviews with the hiring team
- Some recruitment may include an additional assessment or case study stage, or a third stage interview
- If successful, you will receive a conditional offer of employment, followed by your contract subject to passing background checks
We need to keep children and adults safe so our selection process includes rigorous background checks and reflects our commitment to the protection of children and adults from abuse. All employees are expected to carry out their duties in accordance with our Code of Conduct and all policies and procedures relating to Anti\-Harassment, Health and Safety, Safeguarding, and DEI and Equal Opportunities.
Save the Children does not charge a fee at any stage of the recruitment process.
Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 4,317 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At Save the Children, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills Required
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $214,900 based on 6,420 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
Save the Children AI Hiring
Save the Children has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Remote, US.
Remote Work Context
Remote AI roles pay a median of $180,000 across 1,196 positions. About 15% of all AI roles offer remote work.
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (138) are outnumbered by mid-level (2,071) and senior (1,655) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $287,500 median, while Prompt Engineer roles sit at $145,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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