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Location: Ho Chi Minh City, Vietnam Top 3 Reasons To Join Us Competitive Salary International Environment Working on the latest tech for the Insurtech Market Leader About Us At CoverGo, our mission is to empower all insurance companies to make insurance 100% digital and accessible to everyone. We are a leading global no-code insurance platform for health, life, and P&C We’re the winner of the Insurtech of the Year in all of Asia and other awards globally We work with insurance enterprise clients such as AXA, Bupa, MSIG, Dai-ichi, Bank of China Group Insurance, and many more We're an international, diverse team of over 120 people with 30 nationalities and team members working remotely from all over the world We are fully funded and backed by reputable VC funds and strategic institutional investors We have a global presence in Asia, EMEA and the Americas We’ve grown our annualized revenue by over 30x since January 2021 We’re constantly working towards making CoverGo a workplace that you love coming to. We deeply believe that bringing together a diversity of thoughts, expressions, and perspectives is key to building the best culture for equally diverse communities all over the world About the Role As the Lead Full Stack Engineer, you will take on a pivotal role in guiding the design, implementation, and maintenance of our innovative SaaS platform. You will provide technical direction to the team, working across both front-end and back-end technologies, ensuring scalable and efficient software solutions. Collaborate closely with cross-functional teams to understand end-user requirements, optimize application performance, and enforce best coding practices. Your role will encompass mentoring junior developers, driving innovation, and ensuring the continuous growth and success of our platform. What You Will Do Lead the design, implementation, and maintenance of our insurance enterprise software solutions, providing technical direction to the team. Demonstrate expertise in both front-end and back-end technologies, offering guidance on technology selection, architecture, and best practices. Collaborate with product, design, and engineering teams to understand requirements and technical concepts, ensuring cohesive and effective solutions with a seamless user experience. Optimize platform performance to handle large datasets and high user traffic, ensuring a smooth and responsive user experience. Conduct and lead code reviews, enforce best coding practices, and drive the adoption of standards to maintain high code quality. Investigate and promptly address bugs to uphold platform reliability. Ensure security and compliance by following best practices for securing web applications and adhering to relevant regulations. Stay abreast of the latest technologies, frameworks, and best practices, guiding the team in remaining competitive and innovative. Design the platform with scalability and flexibility, accommodating evolving features and changes as the user base grows. Provide mentorship and technical leadership to junior developers, fostering their growth and contribution to the team's objectives. What We Need Proven experience of 8+ years as a Full Stack Engineer, with a track record of leading complex SaaS applications. Minimum 2 years in a lead/manager role, able to guide and ensure development of teams Strong technical background with proficiency in back-end technologies, such as .NET Core, C#, GraphQL, MongoDB, Docker Proficiency in front-end technologies such as Javascript, Vue.js and/or React.js Familiarity with cloud platforms like AWS, Azure, or Google Cloud for building scalable applications Experience with microservices and/or clean architecture Thorough understanding and practical experience with Test-Driven Development (TDD) to ensure robust and well-tested code Experience with unit, integration and function testing using front-end and back-end testing libraries Proficiency in Domain-Driven Design (DDD) principles to create a maintainable and modular architecture that aligns with business domains In-depth knowledge of web security best practices and experience in ensuring compliance with industry regulations Demonstrated experience in performance optimization for high-traffic web applications Experience with container technologies like docker and good understanding of cloud infrastructure and solutions. Experience with agile development methodologies and collaborating with cross-functional teams Excellent problem-solving skills and a proactive approach to troubleshooting and bug fixing Strong communication skills to effectively interact with both technical and non-technical team members with diverse backgrounds A passion for staying updated with the latest trends, technologies, and best practices in software development Why You'll Love Working Here International Environment Competitive remuneration package Hybrid Work Model for those in Ho Chi Minh City; Remote working for those outside Ho Chi Minh City 15 Days Annual Leave 13th-month Pay Annual Performance Bonus Stock Options after 6 months Health Insurance Company activities and events Learning and development plan CoverGo Company Video By submitting your application, you confirm that you have read, understood, and accepted the content of CoverGo’s Privacy Notice and you consent to the processing of your data as part of this application.

Location: Singapore About the Company Our client is a stealth AI startup backed by one of Southeast Asia's leading technology companies and is currently building its global founding team. The company is developing an AI-native communication platform designed to simplify everyday tasks by integrating AI directly into conversations. Instead of switching between multiple applications, users can plan, organize, compare, research, and complete tasks within a single intelligent assistant. Serving a market of billions of users still relying on traditional productivity tools, the platform focuses on delivering reliable AI workflows, persistent context, multi-step reasoning, and seamless task execution. The mission is to create an AI assistant that significantly improves productivity while making everyday work simpler and more intuitive. About the Role Our client is seeking a VP of Research (Machine Learning) to define and lead the research direction behind its AI platform. This leadership role will shape how AI systems reason, learn, evaluate, and continuously improve within a product designed for high-frequency, real-world usage. Working closely with product and engineering leadership, this position will drive the long-term intelligence strategy, balancing cutting-edge research with practical production impact. Key Responsibilities Define and evolve the research roadmap for the platform's core AI intelligence, including context representation, memory, reasoning, planning, and orchestration. Evaluate and determine when to develop proprietary model architectures versus leveraging or adapting frontier open-source and commercial AI models. Design evaluation frameworks that measure real-world performance, robustness, safety, and long-term system behavior beyond traditional benchmark metrics. Lead the company's AI alignment, safety, and guardrail strategy as a core component of product development. Drive research and experimentation across advanced machine learning techniques, including: Retrieval-Augmented Training (RAG) Mixture of Experts (MoE) Model Distillation Multi-Agent Orchestration Multimodal AI Systems Partner closely with product and engineering teams to define and execute the intelligence strategy for AI-powered applications. Establish and maintain high standards for research quality, technical judgment, and engineering excellence across the organization. Requirements Extensive experience designing, building, and deploying machine learning systems in production environments. Strong technical expertise in model behavior, failure analysis, system evaluation, and long-term AI performance. Proven ability to translate advanced research into reliable, production-ready AI solutions. Demonstrated experience making high-impact technical decisions in fast-moving and ambiguous environments. Deep understanding of AI evaluation methodologies, model robustness, safety, and system reliability. Strong ownership mindset with the ability to lead technical strategy and execution. Passion for building practical AI systems that deliver measurable real-world impact rather than focusing solely on academic research or benchmark performance. Preferred Technical Skills Experience with the following technologies is preferred: Python PyTorch and/or JAX GPU-based model training and inference systems

Location: Singapore About the Company Our client is a stealth AI startup backed by one of Southeast Asia's leading technology companies and is currently building its global founding team. The company is developing an AI-native communication platform designed to simplify everyday tasks by integrating AI directly into conversations. Instead of switching between multiple applications, users can plan, organize, compare, research, and complete tasks within a single intelligent assistant. Serving a market of billions of users still relying on traditional productivity tools, the platform focuses on delivering reliable AI workflows, persistent context, multi-step reasoning, and seamless task execution. The mission is to create an AI assistant that significantly improves productivity while making everyday work simpler and more intuitive. About the Role Our client is seeking a Technical Lead, Machine Learning to lead the execution of its AI platform by translating research into scalable, production-ready machine learning systems. This role sits at the intersection of research, infrastructure, and product, with responsibility for ensuring models are trainable, deployable, observable, and optimized for real-world performance. Working closely with research, engineering, and product teams, this position will drive the development of robust ML infrastructure while balancing performance, reliability, latency, and cost. Key Responsibilities Lead the end-to-end execution of machine learning systems, including data pipelines, training workflows, evaluation frameworks, inference architecture, and production deployment. Fine-tune and optimize models using modern techniques such as LoRA, QLoRA, Supervised Fine-Tuning (SFT), Direct Preference Optimization (DPO), and model distillation . Design, build, and operate scalable inference systems with a focus on latency, cost efficiency, and reliability. Develop and maintain data pipelines for both synthetic and real-world training datasets. Build evaluation frameworks to measure model performance, robustness, safety, and bias in collaboration with research teams. Optimize production deployments through GPU utilization, memory efficiency, inference optimization, and scaling strategies. Partner closely with application engineering teams to integrate machine learning systems into backend, desktop, and mobile products. Continuously improve production systems through rapid iteration, monitoring, and data-driven optimization. Requirements Proven experience building and deploying production-grade machine learning systems used by real users. Strong expertise working with large language models and understanding model behavior, limitations, and failure modes. Experience developing scalable ML infrastructure, training pipelines, and inference systems. Strong software engineering skills with the ability to write maintainable, production-quality code. Experience balancing real-world production constraints, including latency, reliability, scalability, cost, and safety. Strong ownership mindset with the ability to independently drive technical initiatives from design through deployment. Excellent communication and collaboration skills, with experience working in cross-functional, high-performing engineering teams. Preferred Technical Skills Experience with the following technologies is preferred: Python PyTorch and/or JAX GPU-based model training and inference systems

Location: Singapore About the Company Our client is a stealth AI startup backed by one of Southeast Asia's leading technology companies and is currently building its global founding team. The company is developing an AI-native communication platform designed to simplify everyday tasks by integrating AI directly into conversations. Instead of switching between multiple applications, users can plan, organize, compare, research, and complete tasks within a single intelligent assistant. Serving a market of billions of users still relying on traditional productivity tools, the platform focuses on delivering reliable AI workflows, persistent context, multi-step reasoning, and seamless task execution. The mission is to create an AI assistant that significantly improves productivity while making everyday work simpler and more intuitive. About the Role Our client is seeking a Senior Machine Learning Engineer to design and build production-grade machine learning systems that power its AI platform. This is a hands-on technical role focused on solving complex machine learning challenges, translating research into scalable solutions, and delivering reliable AI systems that operate effectively in real-world environments. Working closely with research, product, and engineering teams, this position will independently own critical machine learning components from development through production deployment. Key Responsibilities Build and develop core machine learning systems that power AI-driven product capabilities. Own the end-to-end machine learning lifecycle, including data preparation, model training, evaluation, inference, deployment, and continuous iteration. Translate research concepts into reliable, production-ready machine learning solutions. Investigate and resolve model performance issues and production system failures using real-world operational insights. Continuously improve machine learning systems through rapid experimentation, measurement, and iteration. Collaborate closely with research, product, and engineering teams to deliver impactful AI features. Provide technical guidance through code reviews, best practices, and mentorship of fellow machine learning engineers. Develop solutions that balance real-world production requirements, including latency, scalability, cost efficiency, reliability, and safety. Requirements Proven experience building and deploying production machine learning systems used by real users. Strong understanding of modern machine learning models, including their behavior, limitations, and failure modes in production environments. Excellent software engineering skills with the ability to develop robust, maintainable, production-quality systems. Experience designing and implementing scalable machine learning pipelines and infrastructure. Strong ownership mindset with the ability to independently solve complex technical challenges from concept through deployment. Excellent problem-solving, communication, and collaboration skills within cross-functional engineering teams. Demonstrated ability to iterate quickly and continuously improve machine learning systems based on production feedback. Preferred Technical Skills Experience with the following technologies is preferred: Python PyTorch and/or JAX GPU-based training and inference systems

Location: Singapore About the Company Our client is a stealth AI startup backed by one of Southeast Asia's leading technology companies and is currently building its global founding team. The company is developing an AI-native communication platform designed to simplify everyday tasks by integrating AI directly into conversations. Instead of switching between multiple applications, users can plan, organize, compare, research, and complete tasks within a single intelligent assistant. Serving a market of billions of users still relying on traditional productivity tools, the platform focuses on delivering reliable AI workflows, persistent context, multi-step reasoning, and seamless task execution. The mission is to create an AI assistant that significantly improves productivity while making everyday work simpler and more intuitive. About the Role Our client is seeking a Principal Machine Learning Engineer to build and deploy production-grade machine learning systems that power its AI platform. This role focuses on translating research into scalable solutions by developing robust training pipelines, inference systems, evaluation frameworks, and deployment infrastructure. Working closely with research and application engineering teams, this position will play a key role in delivering reliable, high-performance ML systems that operate effectively under real-world production constraints. Key Responsibilities Build and own end-to-end machine learning pipelines covering data processing, model training, evaluation, inference, and deployment. Fine-tune and adapt models using modern techniques such as LoRA, QLoRA, Supervised Fine-Tuning (SFT), Direct Preference Optimization (DPO), and model distillation. Design and operate scalable inference systems while balancing latency, cost, and reliability. Develop and maintain data pipelines for both synthetic and real-world training datasets. Build evaluation frameworks to assess model performance, robustness, safety, and bias in collaboration with research teams. Optimize production deployments through GPU optimization, memory efficiency, latency reduction, and scaling strategies. Collaborate with application engineering teams to integrate machine learning systems into backend, mobile, and desktop applications. Continuously improve ML systems through rapid iteration and real-world performance monitoring while balancing production constraints such as latency, cost, reliability, and safety. Requirements Strong background in deep learning and transformer-based architectures. Hands-on experience training, fine-tuning, or deploying large-scale machine learning models in production. Proficiency with modern machine learning frameworks such as PyTorch or JAX . Experience with distributed training and inference frameworks, including technologies such as DeepSpeed, FSDP, Megatron, ZeRO, or Ray . Strong software engineering skills with experience building robust, maintainable, production-grade systems. Experience optimizing GPU workloads, including memory efficiency, quantization, and mixed precision. Ability to independently own end-to-end machine learning systems in fast-moving environments. Strong problem-solving skills with a focus on rapid iteration and continuous improvement. Preferred Qualifications Experience with one or more of the following is preferred: LLM inference frameworks such as vLLM, TensorRT-LLM, or FasterTransformer Open-source contributions to machine learning or systems libraries Scientific computing, compiler technologies, or GPU kernel development Reinforcement Learning from Human Feedback (RLHF) pipelines, including PPO, DPO, or ORPO Training or deploying multimodal or diffusion models Large-scale data processing frameworks such as Apache Arrow, Spark, or Ray

Location: Singapore About the Company Our client is a stealth AI startup backed by one of Southeast Asia's leading technology companies and is currently building its global founding team. The company is developing an AI-native communication platform designed to simplify everyday tasks by integrating AI directly into conversations. Instead of switching between multiple applications, users can plan, organize, compare, research, and complete tasks within a single intelligent assistant. Serving a market of billions of users still relying on traditional productivity tools, the platform focuses on delivering reliable AI workflows, persistent context, multi-step reasoning, and seamless task execution. The mission is to create an AI assistant that significantly improves productivity while making everyday work simpler and more intuitive. About the Role Our client is seeking an iOS Software Engineer to build and enhance its AI-native mobile experience. This role is responsible for developing production-grade iOS applications where AI interactions are central to the user experience, ensuring performance, reliability, and user trust across all mobile interactions. Working closely with backend and machine learning teams, this position will focus on delivering scalable iOS applications that integrate advanced AI capabilities while maintaining a seamless and intuitive user experience. Key Responsibilities Build and maintain production iOS applications using Swift and SwiftUI . Integrate AI-powered features through backend APIs. Design user experiences for AI interactions, including loading states, streaming responses, retries, and fallback mechanisms. Optimize application performance, memory usage, and battery efficiency. Implement user feedback and analytics mechanisms to support AI evaluation and continuous product improvement. Collaborate closely with backend and machine learning engineers on API design and system behavior. Maintain high standards of application quality, stability, and reliability for App Store releases. Requirements Minimum 3 years of iOS development experience using Swift. Hands-on experience integrating AI-powered features into mobile applications. Strong understanding of async/await , concurrency, and background task management. Solid experience optimizing iOS application performance, memory usage, and responsiveness. Experience developing, releasing, and maintaining production iOS applications. Familiarity with designing applications that operate reliably under latency, partial failures, and non-deterministic AI behavior. Exposure to CoreML or lightweight on-device machine learning is an advantage. Familiarity with feature flags or remote configuration systems is preferred. Strong understanding of user experience design for AI-powered applications, with an emphasis on usability and user trust. Preferred Technical Skills Experience with the following technologies is preferred: Swift SwiftUI Swift Package Manager (SPM) SQL and NoSQL databases TensorFlow Lite (on-device inference)

Location: Singapore About the Company Our client is a stealth AI startup backed by one of Southeast Asia's leading technology companies and is currently building its global founding team. The company is developing an AI-native communication platform designed to simplify everyday tasks by integrating AI directly into conversations. Instead of switching between multiple applications, users can plan, organize, compare, research, and complete tasks within a single intelligent assistant. Serving a market of billions of users still relying on traditional productivity tools, the platform focuses on delivering reliable AI workflows, persistent context, multi-step reasoning, and seamless task execution. The mission is to create an AI assistant that significantly improves productivity while making everyday work simpler and more intuitive. About the Role Our client is looking for a Full Stack Engineer – AI Systems to build AI-native product experiences that transform advanced AI capabilities into intuitive, production-ready workflows. This role combines frontend, backend, and AI engineering to develop intelligent features that are reliable, scalable, and user-centric. Working closely with product, backend, and machine learning teams, this position will focus on designing end-to-end AI workflows, integrating large language models (LLMs), and delivering seamless user experiences across web applications. Key Responsibilities Build end-to-end product features across frontend, backend, and AI integrations. Design and develop AI agent workflows that support planning, tool usage, failure handling, and recovery across multiple steps. Integrate LLMs, memory systems, and external tools into scalable, production-grade applications. Design responsive AI interactions with streaming capabilities, partial results, and low-latency performance. Improve system reliability, observability, and fallback mechanisms for AI-powered features. Collaborate closely with product, backend, and machine learning teams to deliver features from concept to production. Continuously iterate and improve product functionality based on user feedback, production insights, and real-world usage. Requirements Strong experience in full stack software engineering across frontend and backend development. Solid understanding of system design, scalable architecture, and API development. Experience building AI-powered applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), or similar technologies. Ability to work effectively in fast-paced environments with evolving requirements. Strong ownership mindset with experience delivering features from ideation through production deployment. Excellent problem-solving skills and the ability to make pragmatic engineering decisions in ambiguous situations. Preferred Technical Skills Experience with some or all of the following technologies is preferred: Next.js Python Node.js PyTorch OpenAI, Anthropic, or open-source Large Language Models (LLMs) SQL and NoSQL databases Kubernetes Docker

Location: Singapore About the Company Our client is a stealth AI startup backed by one of Southeast Asia's leading technology companies and is currently building its global founding team. The company is developing an AI-native communication platform designed to simplify everyday tasks by integrating AI directly into conversations. Instead of switching between multiple applications, users can plan, organize, compare, research, and complete tasks within a single intelligent assistant. Serving a market of billions of users still relying on traditional productivity tools, the platform focuses on delivering reliable AI workflows, persistent context, multi-step reasoning, and seamless task execution. The mission is to create an AI assistant that significantly improves productivity while making everyday work simpler and more intuitive. About the Role Our client is seeking an Android Software Engineer to build and enhance its AI-native mobile experience. This role is responsible for developing production-grade Android applications where AI is at the core of the user experience, ensuring performance, reliability, and usability across all mobile interactions. Working closely with backend and machine learning teams, this position will focus on delivering scalable Android applications that integrate advanced AI capabilities while maintaining a seamless user experience. Key Responsibilities Build and maintain production Android applications using Kotlin . Integrate AI-powered features such as chat, vision, voice, and recommendation systems through backend APIs. Design intuitive user experiences for AI interactions, including streaming responses, retries, and partial results. Optimize application performance, memory usage, and responsiveness for AI-intensive workflows. Implement analytics, logging, and user feedback mechanisms to support continuous AI evaluation and product improvement. Collaborate closely with backend and machine learning engineers to define API integrations and system behavior. Ensure application stability, security, and scalability within production environments. Requirements Minimum 3 years of Android application development experience using Kotlin. Hands-on experience integrating AI-powered features, such as Large Language Models (LLMs), computer vision, or speech APIs. Strong understanding of asynchronous programming using Coroutines and Flow . Experience working with RESTful or gRPC APIs and structured data formats. Strong debugging, troubleshooting, and performance profiling skills. Experience developing applications that operate reliably under conditions involving latency, partial failures, and non-deterministic behavior. Familiarity with ML Kit or lightweight on-device inference is an advantage. Experience publishing and maintaining production applications on the Google Play Store . Preferred Technical Skills Experience with the following technologies is preferred: Kotlin / Java SQL and NoSQL databases TensorFlow Lite (on-device inference)

Location: Singapore About the Company Our client is a stealth AI startup backed by one of Southeast Asia's leading technology companies and is currently building its global founding team. The company is developing an AI-native communication platform designed to simplify everyday tasks by integrating AI directly into conversations. Instead of switching between multiple applications, users can plan, organize, compare, research, and complete tasks within a single intelligent assistant. Serving a market of billions of users still relying on traditional productivity tools, the platform focuses on delivering reliable AI workflows, persistent context, multi-step reasoning, and seamless task execution. The mission is to create an AI assistant that significantly improves productivity while making everyday work simpler and more intuitive. About the Role Our client is seeking a AI Backend Engineer to build and operate the backend infrastructure that powers AI-driven experiences across its products. The role focuses on owning the inference and orchestration layer that sits between AI models and end users, ensuring every interaction is fast, reliable, scalable, and cost-efficient. Working closely with engineering and AI teams, this position will play a key role in designing production-grade backend services, optimizing system performance, and delivering robust AI-powered features across mobile and desktop platforms. Key Responsibilities Build, maintain, and operate backend systems that power AI-enabled features in production. Design and implement AI inference pipelines, orchestration layers, and service architectures around AI models. Develop scalable, high-performance APIs that integrate seamlessly with frontend applications and machine learning systems. Optimize system performance by improving inference latency, throughput, caching, batching, and streaming capabilities. Own production operations, including monitoring, logging, alerting, and incident response. Troubleshoot and resolve issues within distributed systems to ensure service reliability and stability. Continuously improve backend architecture and production systems based on operational insights and real-world usage. Collaborate with cross-functional teams to deliver reliable, scalable, and high-quality AI-powered solutions. Requirements Strong backend engineering experience in production environments. Proven experience building and operating high-throughput, low-latency backend services. Experience designing scalable APIs and distributed systems. Familiarity with AI inference patterns, including Large Language Models (LLMs), embeddings, and multimodal AI systems. Strong debugging and troubleshooting skills within distributed production environments. Demonstrated ability to deliver production-ready solutions while iterating based on real-world system performance. Excellent analytical, problem-solving, and collaboration skills. Technical Skills Experience with the following technologies is preferred: Python Node.js PyTorch OpenAI, Anthropic, or open-source Large Language Models (LLMs) SQL and NoSQL databases Kubernetes Docker

Location: Lagos, Nigeria Who We Are We're a passionate team determined to challenge the status quo and make financial inclusion count for the millions of under-banked individuals and small business owners in Nigeria. We provide loans, savings, and fixed deposit solutions to our customers. Our vision is to be the most convenient lending company, delivering outstanding service experience. The Role The Senior Risk Analyst (Portfolio Risk) is responsible for driving portfolio risk analytics, credit performance monitoring, Expected Credit Loss (ECL) modeling, impairment analysis, and value-added risk initiatives that optimize portfolio performance and profitability. The role partners closely with Risk, Finance, Product, Collections, and Technology teams to deliver actionable portfolio insights, automate reporting, improve decision-making, and support strategic initiatives such as Risk-Based Pricing (RBP), digitalization, and portfolio optimization. This role is ideal for someone with strong analytical capabilities, deep knowledge of retail lending portfolios, IFRS 9/ECL methodologies, and the ability to translate complex data into business recommendations within a fast-paced financial services environment. What You Will Do Monitor and analyze portfolio performance across all lending products, identifying emerging risks, trends, and business opportunities. Develop, automate, and maintain portfolio risk dashboards, management reports, and executive reporting. Lead value-added portfolio initiatives including Risk-Based Pricing (RBP), digitalization, and portfolio optimization projects. Deliver timely, accurate, and insightful reporting to support strategic and operational decision-making. Own the portfolio Expected Credit Loss (ECL) and impairment analysis in accordance with IFRS 9 requirements. Provide profitability analysis by evaluating impairment costs, portfolio performance, and P&L contribution across each lending product. Support forecasting of credit losses, provisions, and portfolio performance under different economic scenarios. Design and enhance portfolio monitoring frameworks, early warning indicators, and risk performance metrics. Collaborate with Data, Finance, Product, Collections, and Technology teams to improve data quality and reporting automation. Build automated reporting solutions and improve data infrastructure to reduce manual processes. Conduct deep-dive analyses into portfolio trends, customer behavior, segmentation, and credit performance. Perform portfolio stress testing, sensitivity analysis, and scenario modeling. Support regulatory reporting, internal audits, and governance requirements relating to portfolio risk. Recommend risk policy enhancements based on portfolio performance and analytical findings. Maintain documentation for portfolio methodologies, reporting processes, and analytical models. Drive continuous improvement initiatives across portfolio analytics and reporting capabilities. Requirements What You Bring Educational Qualification Bachelor's degree in Statistics, Mathematics, Economics, Finance, Accounting, Computer Science, Engineering, or a related quantitative discipline. Master's degree is an added advantage. Professional Certifications FRM (Financial Risk Manager) – preferred. CFA (Chartered Financial Analyst) – an advantage. ACCA, ACA, or equivalent accounting qualification is beneficial. IFRS 9 or Credit Risk certifications are an added advantage. Microsoft Power BI, SQL, Python, SAS, or Data Analytics certifications are desirable. Experience Minimum of 5–7 years of experience in Portfolio Risk, Credit Risk Analytics, Risk Modelling, or Financial Risk. Experience within banking, fintech, consumer lending, digital lending, or financial services. Demonstrated experience with IFRS 9, Expected Credit Loss (ECL), impairment analysis, and portfolio monitoring. Experience building automated reporting and portfolio dashboards. Experience supporting senior management with portfolio performance insights and strategic recommendations. Professional Competencies Strong knowledge of portfolio risk management principles and retail lending products. Deep understanding of IFRS 9, ECL methodologies, impairment calculations, and provisioning. Strong analytical skills with experience interpreting large datasets and translating insights into business actions. Advanced proficiency in SQL, Excel, Power BI, Tableau, Python, SAS, R, or similar analytical tools. Strong understanding of P&L drivers, portfolio profitability, and financial performance analysis. Experience designing portfolio monitoring frameworks and early warning indicators. Ability to automate reporting processes and improve reporting efficiency. Strong knowledge of credit risk metrics including PAR, Roll Rates, Vintage Analysis, Loss Rates, Recoveries, and Collections performance. Excellent presentation, communication, and stakeholder management skills. Strong attention to detail with the ability to influence strategic decision-making through data. Ability to manage multiple priorities within a fast-paced environment. This Role Is Ideal For You If: You enjoy transforming complex portfolio data into strategic business insights. You are passionate about credit risk analytics, portfolio optimization, and automation. You enjoy improving reporting efficiency through digitalization and data-driven solutions. You thrive in solving complex business problems using analytics. You enjoy collaborating across Risk, Finance, Technology, and Product teams. You want to influence credit strategy and portfolio performance at scale. You May Not Enjoy This Role If: You prefer operational roles over analytical and strategic work. You are uncomfortable working with large datasets and complex financial models. You dislike automation, reporting, or continuous process improvement. You prefer highly repetitive work with limited opportunities for innovation. You are not interested in financial performance, impairment, or portfolio optimization. Benefits What's In It For You Opportunity to shape portfolio strategy within a leading fintech organization. Direct ownership of portfolio analytics, IFRS 9 reporting, and risk insights that influence executive decision-making. Exposure to large-scale digital transformation, Risk-Based Pricing (RBP), and advanced analytics initiatives. Opportunity to collaborate with Risk, Finance, Product, Data, Engineering, and Executive Leadership teams. Continuous learning, professional certification sponsorship, and career development opportunities. Competitive compensation and the opportunity to solve complex, high-impact credit risk challenges.

Location: Lagos, Nigeria Who We Are We're a passionate team determined to challenge the status quo and make financial inclusion count for the millions of under-banked individuals and small business owners in Nigeria. We provide loans, savings, and fixed deposit solutions to our customers. Our vision is to be the most convenient lending company, delivering outstanding service experience. The Role The Senior Anti-Fraud & Credit Policy Manager leads the Bank's Credit Policy and Fraud Prevention function, ensuring robust controls across customer onboarding, loan origination, and portfolio management. The role is responsible for developing and optimizing fraud prevention strategies, KYC controls, credit policy rules, and fraud detection models while safeguarding the business against financial crime and operational losses. The successful candidate will oversee anti-fraud systems, external risk data providers, blacklist management, and continuous monitoring of fraud attacks. Working closely with Risk, Credit, Product, Operations, Technology, Compliance, and Data Science teams, this role will drive automation, enhance decisioning frameworks, and strengthen fraud prevention capabilities across the lending lifecycle. This role is ideal for someone with extensive experience in fraud risk management, credit policy, digital lending, and data-driven decisioning within banking or fintech. What You Will Do Lead the design, implementation, and continuous improvement of credit policies and anti-fraud strategies across all lending products. Develop, monitor, and optimize KYC, customer verification, and fraud prevention controls throughout the customer lifecycle. Design, implement, and fine-tune fraud detection rules, cross-match models, and decision engines to improve fraud detection while minimizing false positives. Manage fraud prevention platforms and decisioning systems to enhance approval quality and customer experience. Oversee relationships with external risk data providers, including credit bureaus, identity verification providers, device intelligence, and fraud intelligence vendors. Evaluate the effectiveness of third-party fraud and identity solutions and recommend enhancements where necessary. Own and maintain customer, device, identity, and merchant blacklists, ensuring timely updates and governance. Monitor fraud trends, emerging threats, attack patterns, and suspicious activities across digital channels. Lead daily fraud monitoring, investigate fraud incidents, and coordinate rapid response actions to mitigate losses. Develop fraud dashboards, KPIs, and management reports to support executive decision-making. Conduct root cause analysis of fraud events and implement preventive controls. Collaborate with Product, Engineering, Data Science, and Operations teams to implement new fraud controls and policy enhancements. Review lending policies and recommend updates based on portfolio performance, fraud trends, regulatory changes, and business strategy. Support internal and external audits, regulatory examinations, and compliance activities relating to fraud prevention and credit policy. Ensure all fraud prevention activities comply with regulatory requirements and internal governance standards. Lead continuous improvement initiatives through automation, analytics, and advanced fraud detection techniques. Requirements What You Bring Educational Qualification Bachelor's degree in Computer Science, Information Technology, Mathematics, Statistics, Economics, Finance, Accounting, Engineering, or a related discipline. Master's degree is an added advantage. Professional Certifications Certified Fraud Examiner (CFE) – preferred. Certified Anti-Money Laundering Specialist (CAMS) – an advantage. Certified Risk Management Professional (CRMP), FRM, or equivalent certifications are desirable. Professional certifications in Data Analytics, SQL, Python, SAS, or Power BI are an added advantage. Experience Minimum of 6–8 years of experience in Fraud Risk Management, Credit Policy, Financial Crime, Credit Risk, or Digital Lending. At least 3 years in a leadership or senior specialist role. Experience within banking, fintech, consumer lending, or financial services. Hands-on experience managing fraud prevention systems, KYC platforms, and rule-based decision engines. Experience working with external fraud intelligence, identity verification, and credit bureau providers. Professional Competencies Strong knowledge of digital fraud prevention, financial crime, and credit policy management. Deep understanding of KYC, Customer Due Diligence (CDD), identity verification, and fraud risk controls. Experience designing and optimizing fraud rules, scorecards, cross-match models, and decision engines. Strong understanding of fraud attack vectors, synthetic identity fraud, account takeover, device fraud, application fraud, and first-party fraud. Experience managing external risk data providers and integrating third-party fraud solutions. Strong knowledge of blacklist management, fraud monitoring, and fraud investigation processes. Proficiency in SQL, Excel, Power BI, Python, SAS, or similar analytical tools. Strong analytical and problem-solving skills with the ability to identify emerging fraud patterns. Excellent stakeholder management, communication, and leadership skills. Strong understanding of regulatory requirements relating to fraud prevention, AML, KYC, and consumer lending. Ability to balance fraud prevention with customer experience and business growth. This Role Is Ideal For You If: You enjoy building robust fraud prevention and credit policy frameworks. You are passionate about protecting customers and the business from financial crime. You enjoy analyzing fraud patterns and improving decision engines through data. You thrive in fast-paced, technology-driven lending environments. You enjoy collaborating across Risk, Compliance, Product, Engineering, and Operations teams. You are motivated by solving complex fraud challenges using analytics and technology. You May Not Enjoy This Role If: You prefer operational processing over strategic risk management. You are uncomfortable making high-impact risk decisions. You dislike working with fraud analytics, rule optimization, and large datasets. You prefer environments with limited change and innovation. You are not interested in regulatory compliance, fraud prevention, or credit governance. Benefits What's In It For You Opportunity to lead fraud prevention and credit policy for a fast-growing fintech organization. Ownership of fraud strategy, KYC controls, and credit decisioning frameworks that directly influence portfolio quality and customer trust. Exposure to advanced fraud technologies, digital identity solutions, and analytics-driven decisioning. Opportunity to collaborate with Risk, Product, Engineering, Data Science, Compliance, and Executive Leadership teams. Continuous learning, professional certification support, and career development opportunities. Competitive compensation and the opportunity to solve complex, high-impact fraud and credit risk challenges.

Location: Lagos, Nigeria Who We Are: We're a passionate team determined to challenge the status quo and make financial inclusion count for the millions of under-banked individuals and small business owners in Nigeria. We provide loans, savings, and fixed deposit solutions to our customers. Our vision is to be the most convenient lending company, delivering outstanding service experience. The Role: The Portfolio Manager is responsible for developing, implementing, and managing credit portfolio strategies that support the Bank's expansion into new markets and regions. The role ensures sustainable portfolio growth by balancing risk, profitability, and customer acquisition while adapting credit strategies to local market dynamics and regulatory environments. This role will lead portfolio performance monitoring, market analysis, credit strategy optimization, and expansion initiatives across multiple geographies. Working closely with Credit Risk, Product, Finance, Data, Collections, and Business teams, the Portfolio Manager will drive data-driven decisions that maximize portfolio quality and business performance. This role is ideal for someone with strong expertise in portfolio management, retail lending, credit analytics, and expansion strategy within banking or fintech. What You Will Do: Develop and execute portfolio strategies to support expansion into new markets and regions. Design localized credit strategies based on customer behaviour, market conditions, regulatory requirements, and portfolio performance. Monitor portfolio quality, profitability, and growth across multiple regions using key credit risk metrics. Analyse portfolio trends, customer segments, and product performance to identify growth opportunities and emerging risks. Perform portfolio forecasting, scenario analysis, stress testing, and profitability assessments. Recommend enhancements to underwriting policies, pricing strategies, and portfolio limits to optimise business performance. Partner with Product and Business teams to support the launch of new lending products and market expansion initiatives. Monitor key portfolio indicators including delinquency, default rates, recoveries, vintage performance, roll rates, and loss trends. Conduct deep-dive analysis on regional portfolio performance and provide actionable recommendations to senior management. Collaborate with Finance on Expected Credit Loss (ECL), impairment analysis, and portfolio provisioning. Develop automated dashboards and portfolio reporting to support executive decision-making. Drive continuous improvement initiatives across portfolio analytics, reporting automation, and risk management processes. Ensure compliance with internal credit policies, regulatory requirements, and governance standards. Work closely with Risk, Data Science, Technology, Collections, and Operations teams to improve portfolio performance and customer outcomes. Requirements What You Bring Educational Qualification: Bachelor's degree or Higher National Diploma in Finance, Economics, Statistics, Mathematics, Business Administration, Engineering, Computer Science, or a related quantitative discipline. A Master's degree is an added advantage. Professional Certifications: Financial Risk Manager (FRM) or Chartered Financial Analyst (CFA) certification is preferred. Professional certifications in Credit Risk Management or Portfolio Management are an added advantage. Microsoft Power BI, SQL, Python, SAS, or equivalent data analytics certifications are desirable. Experience: Minimum of 5–7 years of experience in Portfolio Management, Credit Risk, Credit Analytics, or Retail Lending. Hands-on experience managing consumer lending portfolios within banking, fintech, or other financial institutions. Experience supporting regional expansion, multi-market portfolios, or new market launches is an added advantage. Professional Competencies: Strong understanding of retail lending, portfolio management, and credit risk principles. Experience analysing portfolio performance using key risk and financial metrics. Knowledge of IFRS 9, Expected Credit Loss (ECL), impairment analysis, and portfolio profitability. Strong analytical skills with experience using SQL, Excel, Power BI, Python, SAS, or similar analytical tools. Experience with portfolio segmentation, vintage analysis, roll rates, delinquency monitoring, and stress testing. Strong understanding of lending products, customer behaviour, and market dynamics. Excellent communication, stakeholder management, and presentation skills. Strong commercial acumen with the ability to balance business growth and portfolio quality. Ability to work effectively in a fast-paced, data-driven environment while managing multiple priorities. This Role Is Ideal For You If: You enjoy building and optimising lending portfolios across new markets. You are passionate about using data to drive strategic business decisions. You thrive in high-growth, fast-paced financial services environments. You enjoy collaborating with cross-functional teams to deliver business outcomes. You are motivated by solving complex portfolio and credit risk challenges. You May Not Enjoy This Role If: You prefer operational or administrative work over strategic portfolio management. You are uncomfortable working with large datasets and financial analysis. You dislike balancing commercial growth with risk management. You prefer highly repetitive work with limited opportunities for innovation and strategic thinking. Benefits What's In It For You: Opportunity to lead portfolio strategy for regional expansion within a fast-growing fintech organisation. Exposure to large-scale lending portfolios, market expansion, and strategic growth initiatives. Opportunity to collaborate with Credit Risk, Product, Finance, Data, Engineering, and Executive Leadership teams. Continuous learning, professional certifications, and career development opportunities. Competitive compensation and the opportunity to influence business growth while managing portfolio performance across multiple markets.

Location: Lagos, Nigeria Who We Are: We're a passionate team determined to challenge the status quo and make financial inclusion count for the millions of under-banked individuals and small business owners in Nigeria. We provide loans, savings, and fixed deposit solutions to our customers. Our vision is to be the most convenient lending company, delivering outstanding service experience. The Role: The Credit Policy Analyst is responsible for designing, implementing, and continuously improving credit policies and underwriting strategies for new lending products, including Credit Cards, Credit Lines, Buy Now Pay Later (BNPL), Merchant Financing, and other emerging digital credit solutions. The role partners closely with Credit Risk, Product, Data Science, Fraud, Technology, Finance, and Operations teams to ensure new products are launched with robust credit decisioning frameworks that balance portfolio growth, customer experience, profitability, and risk management. This role is ideal for someone with strong expertise in credit policy development, consumer lending, and data-driven decision-making within a fast-paced banking or fintech environment. What You Will Do: Design and develop credit policies for new lending products, including Credit Cards, Credit Lines, BNPL, Merchant Financing, and other digital lending solutions. Define customer eligibility criteria, underwriting standards, credit limits, pricing strategies, and approval rules for new products. Develop, test, and optimize credit decision rules, scorecards, and policy frameworks to improve portfolio quality and customer acquisition. Monitor the performance of newly launched products and recommend policy enhancements based on portfolio analytics and business performance. Conduct policy simulations, scenario analysis, and impact assessments before implementing credit policy changes. Collaborate with Product, Data Science, Fraud, Engineering, Collections, and Finance teams throughout the product development lifecycle. Analyse customer behaviour, repayment trends, portfolio performance, and profitability to support policy improvements. Recommend changes to approval strategies, credit limits, pricing, and risk controls based on portfolio performance and market trends. Develop automated dashboards, portfolio monitoring reports, and policy performance metrics for management reporting. Support A/B testing and champion/challenger strategies to continuously improve credit decisioning. Ensure all credit policies comply with regulatory requirements, internal governance standards, and the Bank's risk appetite. Maintain comprehensive documentation of credit policies, governance approvals, decision rules, and implementation procedures. Support audits, regulatory reviews, and compliance activities relating to credit policy management. Requirements What You Bring Educational Qualification: Bachelor's degree or Higher National Diploma in Finance, Economics, Statistics, Mathematics, Computer Science, Engineering, Business Administration, or a related quantitative discipline. A Master's degree is an added advantage. Professional Certifications: Financial Risk Manager (FRM), Chartered Financial Analyst (CFA), or equivalent risk management certification is preferred. Credit Risk or Consumer Lending certifications are an added advantage. Professional certifications in SQL, Python, SAS, Power BI, or Data Analytics are desirable. Experience: Minimum of 4–6 years of experience in Credit Policy, Credit Risk, Portfolio Analytics, Consumer Lending, or Lending Strategy. Hands-on experience designing or managing credit policies for retail or digital lending products. Experience within banking, fintech, consumer finance, or other regulated financial institutions. Experience supporting the launch of new lending products is an added advantage. Professional Competencies: Strong understanding of consumer lending, underwriting principles, and credit policy management. Experience developing credit strategies for products such as Credit Cards, Credit Lines, BNPL, Merchant Financing, or unsecured lending products. Knowledge of scorecards, decision engines, credit bureau data, affordability assessments, and risk-based pricing. Strong analytical skills with experience using SQL, Excel, Power BI, Python, SAS, or similar analytical tools. Understanding of portfolio monitoring, IFRS 9, Expected Credit Loss (ECL), and portfolio performance metrics. Experience conducting policy performance analysis, segmentation, champion/challenger testing, and portfolio optimisation. Excellent analytical, communication, and stakeholder management skills. Strong attention to detail with the ability to balance business growth, customer experience, and credit risk. This Role Is Ideal For You If: You enjoy designing credit strategies for innovative lending products. You are passionate about balancing business growth with prudent risk management. You enjoy using data and analytics to improve customer decisioning. You thrive in collaborative, cross-functional product development environments. You enjoy solving complex lending and credit policy challenges. You May Not Enjoy This Role If: You prefer operational or administrative work over analytical and strategic roles. You are uncomfortable making data-driven credit policy recommendations. You dislike working with large datasets, policy optimisation, and performance analytics. You prefer highly repetitive work with limited opportunities for innovation. Benefits What's In It For You: Opportunity to shape the credit strategy for innovative lending products within a leading fintech organisation. Hands-on experience launching and optimising products such as Credit Cards, Credit Lines, BNPL, and Merchant Financing. Exposure to Product, Data Science, Risk, Engineering, Finance, and Executive Leadership teams. Continuous learning, professional certification support, and career development opportunities. Competitive compensation and the opportunity to solve complex, real-world lending and credit risk challenges.

Location: San Francisco Workplace: OnSite 🧠 ABOUT LEGION HEALTH At Legion Health https://legionhealth.com, we believe everyone deserves fast, affordable, and world-class health care, and we’re developing the AI infrastructure to deliver it ourselves at world scale. Legion is building autonomous medical care (the AI doctor), starting with psychiatry. Our AI-native care-delivery platform currently automates 95% of the administrative work required for us to deliver direct patient care. We also recently became the first company ever to receive regulatory authorization to let AI prescribe psychiatric medications https://nypost.com/2026/03/27/business/artificial-intelligence-can-now-prescribe-mental-health-drugs/, allowing us to not only collapse health care’s admin costs but also its clinical labor costs—shifting this industry’s economics from humans to tokens. Our technical moat is hard to copy—we combine rich data, production AI, doctors in the loop, and end-to-end care operations to deliver measurably better care to a clinically complex patient population. This has helped us produce tens of thousands of total visits in just 2 years, all while holding ops costs flat and achieving industry-leading patient NPS and retention. While the last generation of healthcare startups made the existing system incrementally more efficient, Legion is rebuilding full-stack care delivery from first principles. Our vision? A 10X better patient experience that’s higher quality, less expensive, and more scalable than ever before. And a 10X better clinician experience that frees our providers to focus on what matters most: caring for patients. Legion Health is backed by Y Combinator, leading venture capital firms, and founders from Function Health, Modern Health, Everly Health, Trusted Health, Clipboard Health, PatientPing, Sesame Care, Faire, EasyPost, and fuboTV. Join us as we build the future of health care: faster, higher-quality, and more affordable, powered by doctors and AI working together. 📍 ROLE LOGISTICS - Job Type: Full-Time - Role Type: GTM Engineering / Revenue Systems / Provider Partnerships / AI Automation / Data & Attribution - Ideal Experience Level: 5+ years, including 3+ years owning GTM systems, revenue automation, growth engineering, or technical RevOps - Location: In-Person in San Francisco, CA - US Visa Sponsorship: Yes 🚀 THE OPPORTUNITY Legion is hiring a GTM Engineer to build the AI-native commercial and referral infrastructure behind our provider-partnership motion. Your systems will help us identify the right provider organizations, reach the right stakeholders, turn interest into referrals, and move referred patients into care quickly. This is not a traditional RevOps or CRM administration job. You will own the technical architecture from market mapping and outbound through referral intake, attribution, eligibility, onboarding, and partner reporting. You will configure best-in-class tools when they are sufficient and write code or build integrations, agents, and internal products when they are not. You will build both sides of our sales motion. From the bottom up, Legion needs a complete view of every clinic, location, physician, referral coordinator, and office leader in a market. From the top down, we need to map enterprise medical groups, centralized referral teams, executives, clinical leaders, and every stakeholder who can shape a partnership. The system should tell each representative who matters, why they matter, what happened last, and what to do next. You will also engineer the path from referral to care. Referrals may arrive through fax, forms, APIs, tracked links, QR codes, phone calls, or patients who begin online after a provider recommendation. Regardless of channel, Legion must identify the source, resolve the provider and organization, preserve attribution, process the referral, initiate eligibility and onboarding, and synchronize the right data across our CRM, product, analytics, and patient-engagement systems. The right person is a hands-on systems builder with strong product judgment. You should be comfortable choosing a CRM, modeling complex account hierarchies, writing SQL and lightweight production code, integrating APIs, deploying AI workflows, debugging failures, and partnering with sales, product, engineering, data, operations, clinical, compliance, and security teams. Over time, you will help turn provider partnerships into a secure product that makes Legion the easiest specialty care partner in the country: simple to refer patients to, easy to collaborate with, and consistently responsive. ✅ RESPONSIBILITIES AND DELIVERABLES - Select and architect Legion’s provider-partnership CRM—whether HubSpot, Salesforce, Attio, or another AI-native platform—as the source of truth for organizations, locations, stakeholders, opportunities, referrals, ownership, and next actions. - Design a durable account hierarchy that connects individual clinicians, clinic locations, care teams, medical groups, parent organizations, enterprise partnerships, and internal owners without losing history or context. - Build a provider prospecting data layer using NPI and claims data, Definitive Healthcare or similar datasets, public sources, enrichment providers, and Legion’s internal data. - Create account-scoring and territory systems that prioritize targets using geography, specialty, patient volume, payer mix, referral potential, network relationships, and engagement signals. - Build coordinated outbound workflows across email, phone, LinkedIn, direct mail, events, lunch-and-learns, and field sales using tools such as Clay, Apollo, LinkedIn Sales Navigator, sequencing platforms, AI agents, and custom integrations. - Map clinic-level champions and referral coordinators alongside enterprise executives, clinical leaders, operations leaders, and centralized referral teams so Legion can sell from the bottom up and the top down. - Equip sales representatives with accurate contact data, office addresses, account briefs, relationship history, meeting preparation, follow-up automation, and clear next-best actions. - Deploy AI-assisted workflows for account research, stakeholder discovery, enrichment, outreach drafting, call intelligence, CRM updates, and follow-up with appropriate evaluations and human review. - Build an omnichannel referral-ingestion layer that turns fax, forms, APIs, tracked links, QR codes, phone calls, provider handoffs, and patients who begin online after a provider recommendation into structured, traceable records. - Automate referral processing, including document extraction, provider and organization matching, deduplication, completeness checks, routing, exception handling, and audit trails. - Connect referral intake to insurance eligibility and AI-native front-desk workflows for patient outreach, onboarding, and scheduling so referred patients reach the right next step without avoidable delays. - Own end-to-end attribution across the referring clinician, clinic, parent organization, partnership, sales representative, campaign, channel, UTM, QR code, landing page, fax source, and downstream patient journey. - Integrate the provider CRM, Legion’s database, the patient-facing CRM, PostHog, Braze or another lifecycle platform, analytics systems, and custom applications into one coherent data flow. - Partner with product and engineering to build secure provider-facing dashboards and workflows for referral volume, referral status, time-to-contact, scheduling progress, coverage and copay information, and other authorized care-coordination information. - Build compliant workflows that return medical records, care summaries, and status updates to referring care teams through approved fax, secure email, portal, interoperability, or other authorized channels at the right cadence. - Create dashboards and operating reviews for market coverage, stakeholder penetration, outreach performance, pipeline, referral volume, conversion, speed to care, repeat referrals, partner expansion, and revenue impact. - Own production reliability across monitoring, logging, retries, rate-limit handling, identity resolution, testing, versioning, access control, documentation, and recovery when systems fail. - Treat HIPAA, PHI handling, minimum-necessary access, role-based permissions, audit trails, consent, and provider trust as product requirements in every automated workflow. - Make disciplined build-versus-buy decisions, ship useful first versions quickly, and drive adoption through clear playbooks, training, and change management. 🏆 YOU’LL BE SUCCESSFUL IF YOU… - Give Legion a provider CRM and data model that the team trusts as the source of truth. - Create a complete, prioritized map of each market so representatives spend time with the right organizations and people. - Build a repeatable outbound engine that produces qualified provider conversations and pipeline through coordinated digital, field, bottom-up, and top-down plays. - Ensure every referral is captured, processed, routed, and attributed correctly regardless of how it arrives. - Reduce the time from referral to eligibility, patient contact, onboarding, scheduling, and completed care. - Give referring care teams a secure, useful experience that increases trust and repeat referrals. - Remove repetitive research, data entry, document processing, routing, follow-up, and reporting work without sacrificing accuracy or judgment. - Build reliable systems that sales and operations adopt, improve continuously, and measurably increase referral volume, conversion, speed to care, partner retention, and revenue. 🧰 IDEAL BACKGROUND AND SKILLS - 5+ years in GTM engineering, revenue operations, sales operations, growth engineering, business systems, data engineering, internal tools, or another systems-building role close to revenue. - 3+ years directly owning CRM architecture, GTM automation, data pipelines, outbound infrastructure, attribution, or technically complex revenue programs. - Strong technical foundation: advanced SQL plus the ability to write and review production-quality Python, JavaScript, or TypeScript for integrations, automations, and internal tools. - Deep CRM fluency in HubSpot, Salesforce, Attio, or similar, including objects, associations, account hierarchies, lifecycle stages, permissions, routing, reporting, deduplication, and data governance. - Hands-on experience with APIs, webhooks, ETL or reverse ETL, event instrumentation, identity resolution, error handling, observability, and modern data warehouses. - Practical fluency with modern GTM tools such as Clay, Apollo, Definitive Healthcare, LinkedIn Sales Navigator, Outreach, Salesloft, n8n, Make, Zapier, Workato, or equivalent platforms. - Production experience with LLM-powered research, extraction, classification, routing, or agentic automation, including structured outputs, evaluations, monitoring, confidence thresholds, and human-in-the-loop review. - Strong analytical judgment across funnels, attribution, pipeline, conversion, velocity, cohort analysis, experimentation, and revenue impact. - Strong product sense and build-versus-buy judgment. You can turn a messy frontline problem into a coherent system that people trust and use. - Strong preference for experience in healthcare, provider partnerships, referrals, physician networks, field sales, multi-location organizations, or another complex relationship-driven business. - Healthcare and security judgment: disciplined access controls, auditability, minimum-necessary access and data use, consent, and close partnership with compliance and clinical leaders. - Bonus: experience with eFax, referral management, EHR integrations, HL7, FHIR, eligibility, claims, provider directories, or NPI data. - Excellent cross-functional communication. You can translate the needs of a sales representative, referral coordinator, operator, clinician, engineer, analyst, and executive into a system that works. - Low ego, high ownership, and startup intensity. You can diagnose the bottleneck, design the solution, ship a useful version, measure the result, and improve it quickly. 💰 COMPENSATION & BENEFITS - Salary: $140,000 – $260,000, based on experience - Early-Stage Equity: Meaningful ownership in a category-defining company. - Health Insurance: Medical, dental, and vision benefits - Additional Perks: In-person retreats, meal stipends, GTM and revenue-systems tooling budget, learning stipend, AI tooling budget - Time Off: Flexible, unlimited vacation policy - Work Hours: Flexible, with responsiveness around high-impact launches or system issues - Work Setup: In-Person in San Francisco, CA - Impact: Build the technical system that turns partnerships into faster access to high-quality medical care for all. - Autonomy and Learning: Own CRM architecture, provider data, outbound infrastructure, referral workflows, attribution, AI automation, reporting, and partner-facing systems end-to-end. - Growth Opportunities: As Legion scales, this role can grow into Head of GTM Engineering, Head of Revenue Operations, or a broader product and growth leadership role. 📝 HOW TO APPLY AND HIRING PROCESS - Apply here: https://jobs.ashbyhq.com/legionhealth/3a007cb1-faad-4854-a847-e4b77eaf3a42 - Overview of our hiring process: 1. Resume + Application Screen 2. Founder Interview 3. GTM + AI Systems Deep Dive 4. Professional Reference Checks - Estimated time-to-hire: 2 weeks - Start date: ASAP - Hiring manager: Arthur MacWaters 🤝 EQUAL EMPLOYMENT OPPORTUNITY Legion Health is proud to be an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees, contractors, and applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, genetic information, or any other protected characteristic under applicable law. We encourage applicants from all backgrounds to apply.

Location: Abqaiq, Saudi Arabia The Associate Storekeeper / Warehouse Operator is responsible for receiving, storing, issuing, and maintaining inventory while ensuring accurate stock records and efficient warehouse operations. The role supports the smooth movement of materials by following established safety, quality, and inventory control procedures. Key Responsibilities Receive, inspect, and verify incoming materials against purchase orders and delivery documents. Store materials in designated locations following warehouse layout and storage standards. Pick, pack, and issue materials accurately according to approved requests. Perform inventory transactions in the ERP/WMS system and maintain accurate stock records. Conduct routine cycle counts and support periodic physical inventory activities. Monitor stock levels and report shortages, damages, or discrepancies to the supervisor. Ensure proper labeling, identification, and traceability of inventory. Load and unload deliveries using appropriate material handling equipment, where authorized. Maintain warehouse cleanliness, organization, and compliance with 5S standards. Follow company safety policies and use appropriate personal protective equipment (PPE). Qualifications High school diploma or equivalent; a diploma or certification in logistics, warehousing, or supply chain is an advantage. 0 –4 years of experience in warehouse, stores, or inventory operations. Experience with ERP or Warehouse Management Systems (WMS) is preferred. Forklift certification is an advantage (where applicable). Skills & Competencies Knowledge of warehouse operations and inventory control. Basic computer proficiency, including Microsoft Office and ERP systems. Good organizational and time management skills. Strong attention to detail and accuracy. Ability to work in a fast-paced environment. Good communication and teamwork skills.

Location: Dhahran, Saudi Arabia ERAM Talent is seeking a motivated Application Developer to join our client in Dhahran, Saudi Arabia . This is an excellent opportunity for fresh graduates and early-career professionals (0–3 years of experience) who are passionate about software development, secure coding practices, and modern application technologies. The ideal candidate will have a strong foundation in software development, application security, and database concepts, with the ability to develop, test, and maintain secure, high-quality applications. You will work closely with cross-functional teams to design, develop, integrate, and optimize software solutions while ensuring compliance with Oil & Gas industry best practices. Key Responsibilities: Design, develop, test, and maintain secure software applications. Apply secure coding practices and ensure application and database security in line with Saudi Aramco standards. Participate in system design, software architecture, application integration, and cloud-based development. Develop and optimize SQL queries and work with relational databases. Perform software testing, debugging, and performance optimization. Collaborate effectively with clients and internal teams to deliver high-quality solutions. Troubleshoot technical issues and provide innovative software solutions. Requirements Bachelor's degree in Computer Science or a related field. GPA of 3.0/4.0 or 4.0/5.0 . 0–3 years of relevant experience (Fresh graduates are encouraged to apply). Strong understanding of application security, database security, and secure coding principles. Knowledge of software architecture, system design, cloud computing, and application integration. Strong analytical, problem-solving, and communication skills.

Location: San Francisco, CA | Seattle, WA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role We are seeking a Director, Technical Accounting – M&A to join our Finance team at Anthropic. In this role, you will support the company's accounting for mergers, acquisitions, strategic investments, and other complex capital transactions. You will report to the Senior Director, Technical Accounting – M&A As Anthropic continues to scale rapidly and deploy capital into acquisitions, strategic investments, joint ventures, and novel commercial structures, you will be a key technical resource on structuring alternatives, consolidation outcomes, and financial statement impact. You will partner closely with Corporate Development, Legal, Tax, Treasury, FP&A, and leadership to ensure that deal economics are accurately reflected under US GAAP and that positions are defensible to external auditors, valuation specialists, and future regulators. This is a builder role: you'll help operate and continuously sharpen the controls, valuation governance, and close-ready documentation expected of a large accelerated filer, working alongside the Senior Director as the function takes shape. If you thrive on being in the room when deals are shaped — and then making the accounting land cleanly — we want to hear from you. In this role, you will: Execute technical accounting for business combinations, asset acquisitions, joint ventures, and related financing/equity structures Partner with and influence Corporate Dev to steer deal structures toward preferred terms and outcomes Perform accounting due diligence on prospective transactions, advising Corporate Development and leadership on GAAP, control, and earnings implications before terms are finalized Execute end-to-end purchase accounting — acquirer and acquisition-date identification, consideration measurement (contingent consideration, rollover equity, replacement awards), and recognition/measurement of assets, liabilities, and goodwill Execute post-close integration accounting — conforming accounting policies, system/ledger onboarding, working capital true-ups, earn-out remeasurement, and push-down considerations Assess and monitor consolidation and investment classification for investees and structured arrangements — VIE/primary-beneficiary analysis, reconsideration events, equity method, measurement alternative, and fair value through earnings — and support impairment and observable-price-change reviews Manage third-party valuation specialists; review PPA, intangible asset valuations, contingent consideration fair values, and impairment analyses Author and defend technical accounting policies & memoranda; partner closely with external auditors on M&A, investment, and consolidation matters Partner with Tax on deal structuring and ASC 740/basis-difference impacts; with Treasury and Legal on equity, SAFE/convertible, and other financing instruments Help refine the deal-accounting operating model — diligence checklists, Day-1 close playbooks, opening balance sheet procedures, measurement-period tracking, integration workplans, and SOX-ready controls over non-routine transactions Prepare and review transaction-related disclosures for quarterly and annual filings, including pro forma financial information and significance testing Present transaction accounting conclusions and financial statement impacts to leadership and cross-functional stakeholders in clear, decision-ready terms Monitor standard-setting and SEC developments affecting business combinations, consolidation, and investments; support adoption and cross-functional education You may be a good fit if you: Have 10+ years of progressive accounting experience, including 4+ years owning complex M&A and strategic investment accounting transactions end-to-end Hold an active CPA license Bring significant Big 4 experience — ideally in a National Office, Transaction/Deal Advisory, or Capital Markets/Accounting Advisory group — paired with in-house experience at a high-growth or public technology company Have contributed to multiple closed acquisitions and minority/strategic investments, including at least one transaction of meaningful scale or complexity Possess deep command of US GAAP for business combinations, consolidation, equity method, and fair value measurement, with a track record of positions that withstand auditor and regulator scrutiny Are fluent in valuation concepts and can direct and challenge third-party specialists on PPA, contingent consideration, and impairment models Have operated within a deal-accounting or investments-accounting function, contributing to playbook and controls design Communicate effectively with Corporate Development and Legal on structuring trade-offs, translating technical conclusions for cross-functional and senior stakeholders Demonstrate exceptional written and verbal communication, translating complex deal accounting into clear business implications Excel at hands-on technical execution in a fast-paced, ambiguous environment, partnering closely with the Senior Director on strategic judgment calls Are proficient with accounting systems (Workday preferred), consolidation tools, and advanced Excel/modeling Curious about and quick to adopt new AI tools, including Claude and Claude for Finance Strong candidates may also: Have deep, practitioner-level expertise in one or more of the following: Business combinations and asset acquisitions (ASC 805), including contingent consideration, replacement share-based awards, and step acquisitions Consolidation and investment classification (ASC 810, 323, 321), including VIE/primary-beneficiary analysis, basis differences, and the measurement alternative Fair value measurement, acquired financial instruments, and goodwill/intangibles (ASC 820, 815, 825, 350, 360), including impairment testing and IPR&D Have led accounting for carve-outs, divestitures, spin-offs, or legal-entity rationalizations, including standing up SOX-compliant controls over non-routine/complex transactions Have prepared or reviewed pro forma financial information and registration-statement disclosures (Article 11 of Regulation S-X, S-X Rule 3-05/1-02(w) significance testing, S-1 processes) Have experience with novel AI/technology deal structures — acqui-hires, IP/license-heavy transactions, data and compute arrangements, revenue-share partnerships, and strategic investor rights — and are passionate about leveraging AI to accelerate diligence, memo drafting, and close Deadline to apply: None. Applications will be reviewed on a rolling basis. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $230,000 — $300,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: San Francisco, CA | New York City, NY | Seattle, WA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Code RL at Anthropic drives reinforcement learning efforts behind Claude's coding capabilities, creating and scaling agentic coding environments. This is an engineering role with unusual latitude to set technical direction and standards. You'll be part of a team solving the engineering side of research efforts such as embedding with research teams, getting up to speed on their systems and needs, and designing the frameworks, APIs, and infrastructure that let researchers move faster, then rotating off, leaving behind well-oiled systems those teams can understand, own, and maintain themselves. Your remit also includes the ongoing health of production RL runs: maintainable, monitored, and straightforward to triage. The team's problem space spans the client side of sandboxed execution for agentic RL environments, large-scale data processing jobs, the lifecycle of production datasets, and the frameworks researchers build environments on. You won't own all of this yourself, you'll take on the slices where your depth matters most. You'll be a strong fit if you have deep expertise in Python, a refined sense of taste for API and framework design, and hard-won intuition for how complex systems fail — especially silently. You should be comfortable diving into messy research code, finding the load-bearing abstractions, and improving them incrementally while researchers continue to build on top of your work. Key responsibilities Design widely-used APIs, frameworks, and abstractions that other engineers and researchers build on, with careful attention to interface legibility and principled defaults Embed with research teams on a rotational basis: understand their engineering needs, build systems and APIs that support their work, and transfer ownership so teams can maintain those systems after you rotate off Work directly in research codebases, improving reliability and structure without slowing down the research they support Anticipate silent failure modes and prevent them structurally through type safety, well-designed invariants, targeted testing, and refactors that shrink the surface area for bugs Contribute to the reliability of production RL systems, including monitoring, regression detection, and triage tooling Help define engineering standards, review practices, and design patterns for a new team, and mentor researchers and engineers in adopting them Minimum qualifications Deep expertise in Python, including static typing, safe async and concurrency patterns, and writing performant Python code A track record of designing intuitive, safe APIs or frameworks that other engineers or teams adopted and built on Experience working productively in large, evolving, or research-style codebases that you didn't originally write Demonstrated ability to anticipate failure modes — especially silent ones — and prevent them structurally through system design, type safety, and testing Strong written and verbal communication skills, including the ability to explain system designs to collaborators with varied engineering backgrounds Comfort with ambiguity: able to scope your own work from a loosely defined problem and drive it to a maintainable outcome Preferred qualifications Experience building infrastructure, tooling, or frameworks for machine learning research or RL workflows Familiarity with reinforcement learning concepts, agentic systems, or LLM training pipelines Experience building or operating large-scale distributed systems Experience building client libraries or SDKs on top of sandboxed, containerized, or remote execution platforms Experience with large-scale data processing or dataset lifecycle management Experience designing plugin systems or extensible class hierarchies used across an organization Experience embedding with or consulting for other teams, including successfully handing off systems for others to own Experience defining code standards, lint rules, or static verification approaches adopted across multiple teams Prior experience as a technical lead, or setting engineering standards for a team Prior experience maintaining an open source project Representative projects These are examples of the challenges the team tackles; no one person will work on all of them: Design a base RL environment abstraction general enough to be subclassed across a wide range of environments Design a model-tool interface for sandboxed agentic environments that has explicit serialization semantics Partner with the platform teams that own the sandbox runtime to specify low-level features that improve the integrity of agentic coding tasks Design probes that catch sandbox regressions early Design the lifecycle and maintenance scheme for a production dataset Lead a research code refactor replacing loosely structured data containers with equivalents that carry stronger correctness guarantees, without breaking the experiments that depend on them Design lint rules and code-style requirements that favor statically verifiable patterns — including patterns less likely to be overlooked by an LLM reviewing or writing the code — to shrink the surface area for silent bugs Build the access layer that lets researchers discover and reuse data artifacts across teams The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $405,000 — $625,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.