data scientist

senior ai engineer

analytics engineer

applied ai engineer

associate data scientist

applied scientist amazon transportation

Cognizant

Cloud Architect (DevSecOps & LLMOps Engineer)
 Location: London, United Kingdom (Hybrid – 50% work from client office)
 Employment Type: Full-time
 Security Clearance: Must hold or be eligible to obtain UK Security Check (SC) Clearance
 About the Role
 As a Cloud Architect (DevSecOps & LLMOps Engineer) , you will make an impact by designing, building, securing, and operating scalable cloud infrastructure and enterprise Generative AI applications that drive automation, observability, and modern LLMOps practices. You will be a valued member of our Cloud & AI Engineering team and work collaboratively with architects, developers, security teams, and business stakeholders to deliver secure, resilient, scalable, and cost-effective cloud and AI solutions using AWS Bedrock and related technologies.
 
In this role, you will: 
Design, implement, and support secure, scalable AWS infrastructure and AI platforms using Terraform, GitHub Actions, Ansible, ECS/Fargate, and AWS native services.
 Build and operationalise enterprise GenAI solutions using Amazon Bedrock, LLMs, RAG pipelines, vector databases, embeddings, chunking strategies, workflow orchestration (DAG/agentic), and AI observability.
 Develop and maintain CI/CD pipelines, Infrastructure as Code, API integrations, cloud security, IAM governance, monitoring, logging, and production BAU support.
 Configure and manage application observability using Datadog (or equivalent), including dashboards, APM, log analytics, infrastructure monitoring, alerting, and operational health reporting.
 Collaborate with architects, developers, security teams, and business stakeholders to deliver secure, resilient, scalable, and cost-effective cloud and AI solutions.
 What You Need to Have to Be Considered
 Strong hands-on experience with AWS services including Amazon Bedrock, ECS/Fargate, Lambda, EC2, API Gateway, VPC, ALB, IAM, CloudWatch, S3, EFS, DynamoDB, and Neptune, alongside Infrastructure as Code using Terraform.
 Strong experience with DevSecOps practices including GitHub Actions, Ansible, Docker, CI/CD automation, security scanning, secrets management, monitoring, logging, and production support.
 Good understanding of LLMOps concepts including LLMs, RAG, embeddings, chunking, vectorisation, vector databases, semantic search, prompt engineering, workflow orchestration (DAG/LangGraph), AI guardrails, and model evaluation.
 Strong experience with API Management platforms such as Amazon API Gateway, Kong, Apigee, or equivalent — with the ability to design, configure, and implement API proxy workflows, authentication, routing, policies, transformations, and API integrations.
 Strong experience with Datadog (or equivalent monitoring platform) for dashboard creation, application monitoring, alert configuration, APM, log analytics, and performance troubleshooting.
 Excellent communication, stakeholder management, and client-facing skills.
 Bachelor's degree in Computer Science, Engineering, or equivalent practical experience.
 Must currently reside in the United Kingdom.
 Must be available to start within 4 weeks of receiving an offer.
 Must hold or be eligible to obtain UK Security Check (SC) Clearance.
 These Will Help You Stand Out
 Experience with Kubernetes/EKS, Docker, ServiceNow, Jira, GitHub Runners, CloudFormation, Route 53, WAF, EventBridge, Step Functions, and serverless architectures.
 Hands-on experience with Python development for automation, API integrations, scripting, and cloud-native application development.
 Experience building AI data pipelines, including document ingestion, preprocessing, metadata enrichment, chunking, embedding generation, vector indexing, and retrieval workflows.
 Familiarity with AI prompt development, prompt tuning, prompt templates, and prompt evaluation techniques.
 Exposure to vector databases, OpenSearch, LangChain/LangGraph, knowledge graphs (Neptune), cloud networking, security best practices, cost optimisation, and enterprise production support.
 
Additional eligibility requirements: 
<ul>
<li>Candidates must hold or be eligible to obtain UK Security Check (SC) Clearance</li>
<li>Candidates must be available to start within 4 weeks of receiving an offer.</li>
</ul>
We're excited to meet people who share our mission and can make an impact in a variety of ways. Don't hesitate to apply, even if you only meet the minimum requirements listed. Think about your transferable experiences and unique skills that make you stand out as someone who can bring new and exciting things to this role.

Cloud Architect

JPMorganChase

<div>JOB DESCRIPTION 
 
 
Payments sit at the center of the global economy, connecting businesses and consumers around the world. You will join a team driving innovation in this fast evolving space as new technologies reshape how money moves. In this role, you will work at the forefront of modern machine learning and generative AI to deliver meaningful, lasting impact on global finance. You will partner closely with product, operations, risk, and technology teams to turn ideas into measurable outcomes. You will also have opportunities to mentor others and help shape how we build and operate production AI. 
 
As a Vice President Machine Learning Data Scientist in Payments Machine Learning, you will lead the design, development, and production deployment of machine learning applications, including generative AI and agentic systems, on cloud infrastructure. You will own end-to-end delivery from problem framing and experimental design through scalable MLOps, evaluation, governance, and integration with strategic systems. You will help set technical direction, establish reusable patterns, and ensure solutions are reliable, secure, and observable in production. You will mentor engineers and data scientists and translate complex technical work into clear decisions and outcomes for stakeholders.
Job Responsibilities<ul><li>
Lead end-to-end delivery of machine learning and AI solutions for complex payments and banking operations problems, from discovery and framing to production rollout and lifecycle management</li><li>
Develop innovative machine learning solutions, including generative AI and multi-agent approaches, and define evaluation, safety, and monitoring strategies for production use</li><li>
Own production deployment patterns including containerization, continuous integration and delivery, automated testing, model and prompt registries, model and version governance, monitoring and alerting, and rollback strategies</li><li>
Architect and deploy scalable, reliable, and secure machine learning and large language model services integrated with strategic platforms and downstream consumers across APIs, batch, streaming, and event-driven patterns, meeting service level objectives</li><li>
Partner with product, operations, risk and control, and technology teams to influence roadmaps, align on requirements, and deliver data-led transformations</li><li>
Establish reusable, modular data science and machine learning capabilities that scale across use cases, including feature engineering, evaluation harnesses, prompt tooling patterns, agent frameworks, orchestration, and context and memory management</li><li>
Provide technical leadership and mentorship through code reviews, design reviews, best practices, and upskilling across data science and engineering partners</li><li>
Communicate with technical and non-technical stakeholders, translating model outputs into decisions, tradeoffs, and operational plans</li><li>
Maintain strong documentation for approaches, model cards, runbooks, and operational procedures</li></ul>
Required Qualifications, Capabilities, and Skills<ul><li>
Master's degree in a quantitative field, or equivalent practical experience</li><li>
Deep understanding of machine learning fundamentals with strong applied data analysis skills</li><li>
Demonstrated experience designing rigorous evaluation and measurement in real-world settings</li><li>
Demonstrated experience deploying and operating machine learning models in production at scale, including monitoring, drift and performance management, reliability, incident management, and continuous improvement</li><li>
Strong Python software engineering skills, including modular object-oriented design, testing, performance tuning, and debugging</li><li>
Working knowledge of MLOps and LLMOps and distributed systems, including training and serving patterns, batch versus real-time architectures, feature stores, orchestration, and scalable data processing</li><li>
Ability to design intrinsic and extrinsic evaluations aligned with business goals, including offline and online alignment and guardrails for unintended outcomes</li><li>
Experience working in regulated environments with awareness of model risk, controls, privacy and security, and audit-ready documentation</li><li>
Strong stakeholder management and teamwork skills, with the ability to drive outcomes in partnership with cross-functional teams</li></ul>
Preferred Qualifications, Capabilities, and Skills<ul><li>
Experience with NLP and generative AI, including large language models, retrieval-augmented generation, tool and function calling, agentic workflows, multi-agent orchestration, and related evaluation and safety patterns</li><li>
Familiarity with agentic building blocks and standards, including orchestration frameworks, context and memory management, and interoperability protocols such as MCP</li><li>
Experience with machine learning frameworks and data science packages such as PyTorch, TensorFlow, scikit-learn, NumPy, pandas, SciPy, and statsmodels</li><li>
Experience deploying to AWS, including services such as SageMaker and Bedrock, and operating production large language model and machine learning workloads with attention to cost, latency, performance, security, and scaling</li><li>
Experience integrating human-in-the-loop and user feedback signals into iterative improvement, including active learning, preference signals, and labeling strategies</li></ul>
ABOUT US
 
 
J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world's most prominent corporations, governments, wealthy individuals and institutional investors. Our first-class business in a first-class way approach to serving clients drives everything we do. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives. 
<div><div>We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation. 
</div></div> 
 
ABOUT THE TEAM
 
 
J.P. Morgan's Commercial &amp; Investment Bank is a global leader across banking, markets, securities services and payments. Corporations, governments and institutions throughout the world entrust us with their business in more than 100 countries. The Commercial &amp; Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world.</div>

Applied AI ML Data Scientist, Vice President - Payments

Amazon Web Services

<div><h2 class="jobSectionHeader">DESCRIPTION</h2><div>
WWPS Business Operations is seeking a driven and talented Business Operations Analyst to play a critical role within the Worldwide Public Sector Field Sales Operations organization. 
 
This role will serve as an important point of coordination across WWPS Sales, Business Operations, Finance, technical teams, and other cross-functional organizations. The successful candidate will help develop scalable operational mechanisms, generate actionable business insights, create strategic narratives, and support operating cadences that enable growth across the Worldwide Public Sector organization. 
 
Additional key focus of the role will be supporting the development, deployment, and adoption of Generative AI solutions that improve operational productivity, data quality, business visibility, and decision-making. The analyst will partner with business and technical teams to identify high-value use cases, automate recurring activities, and scale successful solutions across WWPS. 
 
Data analysis is central to Amazon&rsquo;s culture, and this role will have a direct impact on business strategy and execution. The analyst will transform complex usage, pipeline, financial, and operational data into clear insights and recommendations for Field Sales Operations, Sales leaders, and senior WWPS leadership. 
 
Success in this position requires strong analytical capabilities, sound business judgment, excellent communication skills, and the ability to work effectively across multiple organizations. The ideal candidate will be comfortable operating in an ambiguous environment, managing multiple priorities, and translating business requirements into scalable processes, reporting mechanisms, and technology-enabled solutions. 
 
Key job responsibilities 
<ul><li>Analyze usage, pipeline, financial, and operational data to generate insights, identify trends, and support data-driven decision-making.</li></ul> 
<ul><li>Leverage GenAI to enhance, develop, and maintain dashboards, reports, and recurring metrics to track business performance and support leadership reviews, while driving adoption of GenAI-enabled reporting and analytics solutions across WWPS.</li></ul> 
<ul><li>Support business planning and operational cadences, including forecasting, pipeline reviews, and performance reporting.</li></ul> 
<ul><li>Partner with cross-functional teams to gather requirements and deliver scalable analytical and reporting solutions.</li></ul> 
<ul><li>Create clear summaries, reports, and narrativees that communicate key findings, risks, and opportunities to stakeholders.</li></ul> 
<ul><li>Identify opportunities to improve processes, data quality, and operational efficiency through automation and analytical tools, including GenAI-enabled solutions.</li></ul> 
<ul><li>Support ad hoc analysis and strategic initiatives for Sales and Business Operations teams across WWPS.</li></ul> 
Basic qualifications 
 
Experience in finance, business management and sales operations 
Bachelor's degree in Business Administration, Finance, Economics, Computer Science, Engineering, or related field 
Experience with sales CRM tools such as Salesforce or similar software 
Experience defining, refining and implementing sales processes, procedures and policies or equivalent 
Preferred qualifications 
 
5+ years of finance, business management and sales operations experience 
Experience working within a high-growth, technology company</div><h2 class="jobSectionHeader">
BASIC QUALIFICATIONS</h2><ul><li>Experience with sales CRM tools such as Salesforce or similar software</li><li>Experience using Microsoft Excel to manipulate and analyze data</li><li>Experience defining, refining and implementing sales processes, procedures and policies or equivalent</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>Experience working within a high-growth, technology company</li><li>Experience in finance, business management and sales operations</li></ul> 
Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates. 
 
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. 
 
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner.</div>

Business Operations Mgr, UKGI AWS SMGS Ops Sales Ops-WWPS

Arrows

<div>
 
 
 Forward Deployed Engineer | Applied AI Systems
 
 
 
 
 
 
 I am partnering with a early-stage aviation AI business building
 
 deeply integrated, real-world systems
 
 . Their platform is bespoke, embedding directly into customer environments to
 
 solve real workflow challenges
 
 through AI and data-driven solutions.
 
 
 
 
 
 Backed by
 
 Y-Combinator
 
 and already working with some of the
 
 world's largest brands in their sector
 
 , the company is now scaling its
 
 Forward Deployed Engineer
 
 team to work closely with customers, owning end-to-end delivery of high-impact systems in production.
 
 
 
 
 
 
 Responsibility:
 
 
 
 &bull; Working
 
 directly with customers
 
 
 
 &bull;
 
 Leading integrations
 
 and onboarding across complex technical environments
 
 
 &bull; Rapidly prototyping and
 
 deploying solutions
 
 in live production settings
 
 
 &bull; Translating real-world problems into
 
 scalable AI and engineering solutions
 
 
 
 
 
 
 
 Experience:
 
 
 
 &bull; Strong engineering fundamentals with
 
 hands-on experience building
 
 production systems
 
 
 &bull; Background in AI, data, systems, or product engineering
 
 
 &bull; Comfortable operating in
 
 fast-paced
 
 environments
 
 
 &bull; Experience in
 
 customer-facing
 
 or highly applied engineering roles
 
 
 &bull; Strong programming skills (Python, TypeScript preferred)
 
 
 
 
 
 
 Key responsibilities:
 
 
 
 &bull; Own delivery of customer deployments
 
 
 &bull; Build and iterate on
 
 bespoke integrations
 
 
 
 &bull; Work on-site with users
 
 
 &bull; Collaborate across
 
 engineering and product
 
 to deliver high-impact solutions
 
 
 &bull; Operate with
 
 high ownership in a fast-moving
 
 , early-stage environment
 
 
 
 
 
 
 On offer:
 
 
 
 &bull; High-ownership role within a small, high-calibre team
 
 
 &bull; Opportunity to work directly with customers and build in real-world environments
 
 
 &bull; Significant travel across global customer sites (US &amp; Europe)
 
 
 &bull; Salary up to &pound;140,000 plus substantial equity options
 
 
 &bull; Fast-paced, high-impact environment with direct exposure to leadership
 
 
 
 
 
 If this aligns with your background or interests, feel free to get in touch directly.
 
</div>

Software Engineer

Moss

<div>At Moss, we give finance professionals the power to automate their day-to-day and make forward-thinking decisions.
Our team and culture make us unique &mdash; we&rsquo;re driven by impact and growth, where every one of us strives to learn and excel. Recognised by Sifted&rsquo;s Rising 100 and LinkedIn's Top Startups, we&rsquo;re here to help propel your career and together, make Moss a lasting success.
We are hiring an Applied AI Engineer to design, build, and deploy AI-powered products that transform how finance teams work. You will work with frontier language models to create intelligent services, agents, and workflows that deliver real customer value.<h2 class="jobSectionHeader">
Your Responsibilities</h2><h3 class="jobSectionHeader">
Build AI-Powered Products</h3><ul><li>
Design, develop, and deploy AI-enabled applications and services using state-of-the-art language models.</li><li>
Build intelligent agents and workflows that automate complex finance processes.</li><li>
Experiment with new AI capabilities and rapidly turn prototypes into production-ready features.</li></ul><h3 class="jobSectionHeader">
Evaluate and Improve AI Systems</h3><ul><li>
Develop robust evaluation frameworks to measure quality, reliability, and business impact.</li><li>
Improve model performance through prompt engineering, retrieval-augmented generation (RAG), and other applied AI techniques.</li><li>
Ensure AI systems are accurate, trustworthy, and deliver a high-quality user experience.</li></ul><h3 class="jobSectionHeader">
Design for Trust and Control</h3><ul><li>
Build AI systems that are transparent, auditable, and allow users to review and intervene when needed.</li><li>
Incorporate customer data into AI workflows while maintaining security and privacy standards.</li></ul><h3 class="jobSectionHeader">
Collaborate Across Functions</h3><ul><li>
Partner closely with product managers, designers, engineers, and finance experts to deliver customer-facing AI solutions.</li><li>
Help shape Moss's AI product strategy and engineering best practices.</li></ul><h2 class="jobSectionHeader">
About You</h2><ul><li>
Degree in Computer Science, Mathematics, Engineering, or a related field.</li><li>
Minimum 4 years of professional engineering experience building and shipping production applications.</li><li>
Proven experience working with modern LLMs and AI application development.</li><li>
Strong programming skills in both Python and Java.</li><li>
Experience building backend services and APIs.</li><li>
Hands-on experience with AI agents, RAG systems, prompt engineering, or related applied AI techniques.</li><li>
Ability to balance rapid experimentation with production-quality engineering.</li><li>
Excellent problem-solving and communication skills.</li></ul><h2 class="jobSectionHeader">
Relevant Technologies</h2>
Candidates should have experience with a subset of the following technologies and be eager to learn others.<h3 class="jobSectionHeader">
AI &amp; Machine Learning</h3><ul><li>
Frontier LLMs: OpenAI, Anthropic, Gemini, Llama, Mistral, or similar</li><li>
Agent and orchestration frameworks: LangChain, LlamaIndex, Haystack, or similar</li><li>
Retrieval-Augmented Generation (RAG)</li><li>
Prompt engineering and evaluation methodologies</li><li>
Fine-tuning and model adaptation techniques</li></ul><h3 class="jobSectionHeader">
Software Engineering</h3><ul><li>
Python and Java</li><li>
REST APIs and backend application development</li><li>
SQL and modern data storage technologies</li><li>
Distributed systems and scalable application design</li></ul><h3 class="jobSectionHeader">
Nice to Have</h3><ul><li>
Experience building customer-facing AI products</li><li>
Experience in fintech, finance, or enterprise software</li><li>
Experience with cloud-based AI platforms such as Vertex AI, OpenAI, or Anthropic APIs</li></ul>
About Moss
Moss is the Finance AI platform for Europe's mid-sized businesses, giving companies real-time visibility and full control over their spend. By automating card issuing, invoice management and expenses, Moss simplifies financial workflows and frees finance and accounting teams from manual, administrative work.
Founded in Berlin and used by more than 5,000 businesses including Flink, Schufa, Gusto and Auto1, Moss has raised &euro;200+ million to date and operates in Germany, the Netherlands, the UK and further EU markets. Moss is backed by the most renowned tech investors including Valar Ventures, Tiger Global, Global Founders Capital, Cherry Ventures, A-Star and Portage.
We have a team of 300+ people from 50+ nationalities in 5 offices across Europe. Be part of a culture that thrives on impact and speed, where you can take bold moves, learn fast and accomplish more. We&rsquo;re a place where you can fast track your career - here's what else to expect:<ul><li>
Top-of-market compensation package, including equity.</li><li>
Our vibrant offices are at the heart of our culture, where in-person time fuels collaboration and connection over weekly breakfasts and Friday demos.</li><li>
Additional benefits include: 20 days &ldquo;work from abroad&rdquo;, 600EUR/GBP Learning &amp; Development Budget, and other local benefits.</li></ul>
Unless stated otherwise, benefits apply to full-time positions (interns and working students receive a tailored package).
By applying for the above position, you will confirm that you have reviewed and agreed to our Data Privacy Policy.</div>

Applied AI Engineer

Scale AI

<div>
 
 Machine Learning Engineer
 
 
 
 London, UK
 
 
 
 About The Role
 
 
 
 Applied Intelligence Systems (AIS) is part of the Scale Generative AI Platform (SGP), focused on pushing the frontier of what agentic applications can do across diverse enterprise and government use cases. We build the infrastructure and tooling that power agentic AI in production, paired with applied ML research, design, and evaluation to ensure these systems perform reliably at the scale our customers demand. AIS spans multiple workstreams &mdash; agent evaluation and oversight, orchestration and tool-use infrastructure, model and systems optimization, and applied research on new agent capabilities. This role owns the context and memory capabilities within AIS, including their correctness, performance, and evaluation.
 
 
 We are looking for a Machine Learning Engineer who can own hard technical problems end to end &mdash; from research and prototyping through to production deployment &mdash; working across knowledge bases, vector stores, RAG pipelines, and context engines to power agents that deliver real impact for enterprise customers.
 
 
 
 What You'll Do
 
 
 
 <ul>
 <li>
 Own large areas of the platform end to end, from design through to production deployment.
 </li>
 <li>
 Work on knowledge representation systems, including ontologies and knowledge graphs, to support structured reasoning over enterprise data.
 </li>
 <li>
 Design and implement RAG pipelines, including chunking, embedding, indexing, retrieval, and reranking.
 </li>
 <li>
 Build and maintain integrations between retrieval and ML components and diverse enterprise data sources, vector databases, APIs, and services.
 </li>
 <li>
 Develop context retrieval systems that balance recall, precision, latency, and cost.
 </li>
 <li>
 Build evaluation frameworks, datasets, and metrics to measure retrieval quality, context relevance, and end to end agent performance.
 </li>
 <li>
 Build reliable backend services and data pipelines that support ML and LLM components in production.
 </li>
 <li>
 Deliver experiments and new capabilities quickly, maintaining high quality and tight feedback loops with customers.
 </li>
 <li>
 Collaborate across product, ML, and infrastructure teams to shape the direction of the platform.
 
 
 </li>
 </ul>
 
 What We Look For
 
 
 
 <ul>
 <li>
 5+ years of experience building and deploying machine learning or AI systems for real-world, production use cases.
 </li>
 <li>
 Strong engineering fundamentals, supported by a Master&rsquo;s or PhD degree in Computer Science, Machine Learning, AI, or equivalent practical experience..
 </li>
 <li>
 A deep, hands-on understanding of retrieval systems, RAG, embeddings, vector indexing, knowledge representation, and semantic search.
 </li>
 <li>
 Proven proficiency in Python, including writing production-quality, testable, and maintainable code.
 </li>
 <li>
 The ability to operate in ambiguous problem spaces, balancing research-driven approaches with pragmatic product constraints.
 </li>
 <li>
 Strong communication skills and comfort working in customer-facing or cross-functional environments.
 </li>
 <li>
 Experience scaling products at hyper growth startups
 
 
 </li>
 </ul>
 
 
 PLEASE NOTE:
 
 
 
 Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.
 
 
 
 
 About Us:
 
 
 
 
 At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta,
 
 
 Ernst
 
 
 &amp;
 
 
 Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications.
 
 
 
 
 We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.
 
 
 
 
 We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's
 
 
 Know Your Rights poster
 
 
 for additional information.
 
 
 
 
 We comply with the United States Department of Labor's
 
 
 Pay Transparency provision
 
 
 .
 
 
 
 
 
 PLEASE NOTE:
 
 We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants&rsquo; needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.
 
</div>

Machine Learning Engineer, Platform

International Rescue Committee

<div>The International Rescue Committee (IRC) responds to the world's worst humanitarian crises, helping to restore health, safety, education, economic wellbeing, and power to people devastated by conflict and disaster. Founded in 1933 at the call of Albert Einstein, the IRC is one of the world's largest international humanitarian non-governmental organizations (INGO), at work in more than 40 countries and 29 U.S. cities helping people to survive, reclaim control of their future and strengthen their communities. A force for humanity, IRC employees deliver lasting impact by restoring safety, dignity and hope to millions. If you're a solutions-driven, passionate change-maker, come join us in positively impacting the lives of millions of people world-wide for a better future.
The International Rescue Committee (IRC) responds to the world's worst humanitarian crises, helping to restore health, safety, education, economic wellbeing, and power to people devastated by conflict and disaster. Founded in 1933 at the call of Albert Einstein, the IRC is one of the world's largest international humanitarian non-governmental organizations (INGO), at work in more than 40 countries and 29 U.S. cities helping people to survive, reclaim control of their future and strengthen their communities. If you're a solutions-driven, passionate change-maker, come join us in positively impacting the lives of millions of people worldwide for a better future.
Background:
Build the AI systems that will reach hundreds of millions of people in the world's hardest places.
Nearly 240 million people will need humanitarian aid in 2026, and global funding has fallen by more than half. Closing that gap demands a different kind of humanitarian organization &mdash; one that uses AI to multiply what frontline workers can do, reaches people before crises hit, and brings diagnostic and decision-support tools to places the technology industry has historically ignored.
The International Rescue Committee (IRC) is already one of the most ambitious AI-deploying humanitarian organizations in the world. We are working on dozens of AI initiatives across 30+ countries: agentic systems serving millions of displaced people through Signpost; anticipatory action models that deliver aid in advance of a disaster; pocket-sized AI diagnostics and AI teaching mentors. We have strategic partnerships with AI partners and a portfolio of programs ready to scale.
We are hiring a Head of AI Engineering to lead the technical team that builds these systems &mdash; and to help shape what we build next.
Job Overview:
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 &mdash; 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 &mdash; 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 &mdash; 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.
Major Responsibilities
AI Strategic Leadership<ul><li>
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 &amp; Culture, and the T4P demand pipeline.</li><li>
Stay at the edge of AI/ML advances &mdash; particularly in agentic systems, multimodal models, and edge/on-device inference &mdash; and bring promising approaches to IRC's programs.</li><li>
Serve as a core member of IRC's AI leadership, helping shape organizational direction alongside the SVP for Research, Innovation, AI, and People &amp; Culture and other senior leaders.</li><li>
Champion responsible, human-centered AI deployment in some of the most sensitive humanitarian contexts in the world, with the safety standards those contexts demand.</li><li>
Represent IRC in technical discussions with partners, peer organizations, donors, and the broader humanitarian and AI sectors.</li></ul>
Team Leadership and Management<ul><li>
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.</li><li>
Establish engineering quality standards, development practices, and documentation protocols.</li><li>
Maintain a prioritized backlog of program innovations and manage team capacity against demand.</li><li>
Mature the team's AI development and DevOps practices and grow stakeholder buy-in across the organization.</li><li>
Identify opportunities to secure budget resources in support of innovation priorities.</li></ul>
Cross-functional Partnership<ul><li>
Act as a genuine thought partner to program leaders &mdash; bringing AI fluency to their problems and humility about the field realities</li><li>
Co-design solutions that actually work in the field, not technology-first answers in search of problems.</li><li>
Partner with the Enterprise Applications team to ensure smooth handoffs of proven innovations for enterprise-wide scale-up.</li><li>
Coordinate with the Enterprise Applications DevOps team on integration touchpoints, infrastructure dependencies, and shared engineering standards.</li></ul>
Flagship AI Partnerships<ul><li>
Serve as the technical lead on IRC's strategic partnerships with frontier AI organizations &mdash; helping turn early relationships into long-term, high-leverage collaborations.</li><li>
Identify where partnership access (compute, frontier models, technical expertise) can unlock outsized program impact.</li></ul>
Solution Design and Engineering<ul><li>
Lead the design and development of AI-driven and program-specific technology solutions, owning the full development lifecycle from requirements through handoff.</li><li>
Interface with program and business stakeholders to gather requirements, define technical solutions, and recommend approaches grounded in a detailed understanding of program goals.</li><li>
Design and oversee high-availability architectures in Microsoft Azure, incorporating appropriate redundancy, security, backup, and recovery strategies &mdash; including for sensitive humanitarian data.</li><li>
Research and recommend technology products, services, and standards &mdash; particularly in AI/ML &mdash; to support procurement, development, and strategic decision-making.</li></ul>
DevOps and Engineering Operations<ul><li>
Oversee deployment pipelines, CI/CD automation, infrastructure-as-code, and QA processes to ensure efficient and reliable software delivery.</li><li>
Ensure ongoing availability and performance of applications through monitoring, scaling, and proactive operations management.</li><li>
Track and optimize cloud and model-inference costs.</li><li>
Maintain technical and policy documentation for all assets under the team's management.</li></ul>
Key Working Relationships<ul><li>
Position Reports to: Chief Information Officer, working in close partnership with the SVP for Research, Innovation, AI, and People &amp; Culture</li><li>
Position directly supervises: Engineers, applied AI engineers, ML specialists, and QA staff on the T4P Development team.</li><li>
Other internal contacts: Program leaders across CRRD, RAI, R&amp;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.</li><li>
External contacts: Strategic partners with leading AI organizations; technology vendors; AI sector peers; NGO tech community; major foundation funders.</li></ul>
Job Requirements
Strong candidates will bring most &mdash; not necessarily all &mdash; of the following:
AI and engineering depth<ul><li>
Hands-on experience building and shipping production AI systems &mdash; agentic frameworks, LLM applications, RAG systems, computer vision, or applied ML pipelines.</li><li>
Solid full-stack foundation (Python, JavaScript/TypeScript, and modern frameworks) with the technical credibility to engage directly with engineers on architecture and design decisions.</li><li>
Experience with cloud architecture (Azure preferred; AWS/GCP transferable), including AI services, DevOps pipelines, and cost-effective scaling.</li><li>
Working knowledge of data security and privacy practices for sensitive or personally identifiable information.</li></ul>
Leadership and collaboration<ul><li>
7&ndash;10+ years in software engineering or technical product development, with 3+ years leading engineers as a manager or tech lead.</li><li>
A track record of building or growing strong engineering teams &mdash; hiring, raising the bar, and creating a culture people want to be part of.</li><li>
Ability to engage non-technical leaders as a peer: explaining trade-offs clearly, listening well, and translating between worlds.</li><li>
Comfort operating across global teams, time zones, and contexts very different from your own.</li></ul>
Mindset<ul><li>
Genuinely motivated by humanitarian impact</li><li>
Leads with humility. Deep respect for the people closest to the problem, including those without technical backgrounds.</li><li>
Technically curious and forward-looking &mdash; reads, experiments, and brings new ideas to the team.</li></ul>
Nice to have<ul><li>
Experience deploying AI in low-resource, low-bandwidth, or offline contexts.</li><li>
Prior work with humanitarian, development, or global health organizations.</li><li>
French or Arabic language skills.</li></ul>
Working Environment
Standard office work environment; hybrid/remote available. Some travel may be required for partner meetings, field engagement, and sector conferences.
Compensation: (US Pay Rate: 185,000-200,000 USD); (UK Pay Rate: 87,000-100,000 GBP) 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. 
Professional Standards: All International Rescue Committee workers must adhere to the core values and principles outlined in IRC Way - Standards for Professional Conduct. Our Standards are Integrity, Service, Equality and Accountability. In accordance with these values, the IRC operates and enforces policies on Safeguarding, Conflicts of Interest, Fiscal Integrity, and Reporting Wrongdoing and Protection from Retaliation. IRC is committed to take all necessary preventive measures and create an environment where people feel safe, and to take all necessary actions and corrective measures when harm occurs. IRC builds teams of professionals who promote critical reflection, power sharing, debate, and objectivity to deliver the best possible services to our clients. 
Cookies: https://careers.rescue.org/us/en/cookiesettings 
Equal Opportunity Employer: IRC is an Equal Opportunity Employer. IRC considers all applicants on the basis of merit without regard to race, sex, color, national origin, religion, sexual orientation, age, marital status, veteran status, disability or any other characteristic protected by applicable law.</div>

Head of AI & Program Technology Engineering

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