Submit Cvs – Latest Recruitment
Full-Time
ADG is a global strategic technology firm that helps organisations scale intelligently, efficiently and securely. With teams across Africa, the Middle East and Europe, we combine world-class engineering with deep business understanding. We deliver transformation through three integrated models: advisory, implementation and managed services. This approach Product Manager About the Role We are looking for a sharp, technically fluent Product Manager to bridge the gap between our customers, our advisory team, and engineering, turning real-world client needs; for both our internal products and solutions we build for customers, into products that ships. This isn’t a role where you write specs and wait. You will dig into the technical weeds with engineers, work closely with our advisory team to understand what customers actually need, and use AI tools to move faster from insight to shipped feature. At times, you’ll step into the Product Owner seat on behalf of a customer who doesn’t have one; driving backlog and priorities directly for their engagement. You’ll also get hands-on, mocking up flows in Figma and building quick proof-of-concepts to make the product vision tangible before a single line of production code is written. If you’re excited about owning outcomes rather than outputs, translating messy customer requirements into clear priorities, and using AI as a genuine extension of how you work, this role is for you. Key Responsibilities Bridge Customer, Advisory & Engineering: Act as the connective tissue between our customers, our advisory team on the front lines, and the engineers building the solution, ensuring nothing gets lost in translation. Own Internal & Customer Roadmaps: Define and prioritise the product roadmap across our own internal products as well as active customer engagements, balancing strategic bets against near-term delivery commitments. Proxy Product Owner: Step in as the de facto Product Owner for customers who lack one, owning their backlog, prioritisation, and day-to-day product decisions on their behalf. Requirements Translation: Work directly with the advisory team and customers to turn technical and business requirements into clear epics, user stories, and acceptance criteria engineering can build from. Design & Rapid Prototyping: Mock up flows and screens in Figma, and build quick proof-of-concepts and clickable prototypes to demonstrate product vision, whether for an internal tool or a customer solution. Cross-functional Delivery: Partner closely with engineering to ship features end-to-end, unblocking teams and making fast, well-reasoned trade-off calls. Customer & Market Insight: Join customer conversations directly to identify gaps, validate solutions, and stay close to what customers actually need versus what they initially ask for. AI-Native Workflow: Use AI tools to accelerate research synthesis, spec writing, prototyping, and data analysis, and know where human judgment has to take over. Product Feedback Loop: Serve as the internal voice of the customer, feeding real field insight from the customer and advisory team back into engineering priorities, and back into how our own internal products evolve. What We’re Looking For Core Expertise Track Record: 5+ years of product management experience, ideally in enterprise B2B software or client-facing technical delivery. Product Owner Range: Comfortable operating as a Product Owner when needed, running backlog grooming, writing acceptance criteria, and making the calls a customer’s own Product Owner would normally make. Design & Prototyping: Hands-on experience in Figma (or similar), able to go from idea to clickable mockup or working POC without waiting on a designer or engineer. Technical Fluency: Comfortable reading architecture diagrams, understanding APIs and integrations, and holding your own in a conversation with engineers; you don’t need to write production code, but you need to understand what’s hard and why. Data-Driven Decision Making: Confident using data and experimentation to prioritise, validate hypotheses, and measure impact. AI Fluency: Genuine, daily use of AI tools in your workflow, not just familiarity, but a track record of using them to ship faster and think better, with a mindset of sharing to enable other colleagues to learn from your workflow. Stakeholder & Delivery Skills Executive Presence: Able to move seamlessly between a whiteboard session with engineers and a strategic conversation with a customer’s VP or CTO. Ownership & Bias to Action: High autonomy and grit; you invent solutions rather than waiting for direction. Communication: Exceptional written and verbal skills, with a track record of building trust across technical, advisory, and customer stakeholders alike. Range: Comfortable switching context between shaping our own internal products and driving priorities for customer engagements. Nice-to-Haves Experience in specialised domains relevant to our work (AI/ML products, Mobile, SaaS or other web-application technologies, distributed systems, etc.). Prior experience in a technical, high-touch client delivery environment: forward deployment, solutions engineering, consulting, or technical pre-sales adjacent roles. Formal certifications e.g. Product Owner certification (CSPO or equivalent) or hands-on Scrum/Agile ceremony experience. Background in financial services, payments, or FinTech, with an understanding of the sector’s security and regulatory demands. Experience using AI coding tools (e.g. Claude) to build functional POCs, specifications, etc. What Success Looks Like in Year 1 First 90 Days: Deeply understand our customer base, our advisory team’s workflow, and the engineering process; ship your first roadmap decision backed by real customer and advisory insight. 6 Months: Become the trusted go-to person for customers, advisory, and engineering, with a roadmap that’s respected by all three. 1 Year: Drive measurable customer outcomes through solutions that solve real problems, with a repeatable, AI-accelerated way of working baked into how the team operates. Forward-Deployed Engineer About the Role We are looking for a highly accomplished, deeply technical Senior Forward Deployment Engineer to serve as the dedicated technical engine and trusted advisor for a strategic enterprise client. In this role, you will not just consult from the sidelines; you will sit on the front lines. You will own the technical relationship end-to-end, serving as the client’s go-to technical expert, architecting complex Proofs of Concept (PoCs), building hands-on demos, and solving complex architecture and integration challenges in real time. If you thrive at the intersection of production-grade engineering, complex problem-solving, and high-impact client engagement, this role is for you. If you’re not scared to use AI to help guide your, and our, work, this role is for you. If you’re excited at the prospect of stepping across traditional role boundaries towards things like building agents, product ownership and requirements analysis, this role is for you. Key Responsibilities Dedicated Technical Advisory: Act as the primary, high-touch technical authority and advisor for a key enterprise customer, translating complex technical capability into strategic client value. Account Expansion & Sales Vigour: Proactively identify technical gaps and new business opportunities within the account. Partner closely with the presales team to put together future architectures, pitch new solutions, and drive the expansion of our platform. Rapid Prototyping & PoCs: Scope, design, and build custom demos, production-grade prototypes, and Proofs of Concept (PoCs) directly tailored to the customer’s unique ecosystem and edge cases. Architecture & Integration: Work hands-on with the customer’s engineering, security, and infrastructure teams to design seamless deployment pipelines, custom integrations, and data flows, with a heavy emphasis on Google Cloud Platform (GCP) environments. Real-time Technical Problem Solving: Unblock customer engineering teams by debugging complex deployment, infrastructure, integration, or performance issues on the fly. Product Feedback Loop: Serve as the direct bridge between the customer’s engineering requirements and our internal Product & Core Engineering teams, advocating for features that drive enterprise adoption. What We’re Looking For Technical Expertise Senior Engineering Track Record: 10+ years of hands-on experience in software engineering, backend systems, cloud architecture, or site reliability engineering (SRE). Hands-on Coding: Strong proficiency in modern enterprise programming languages (e.g. Python, Java, TypeScript/Node.js, or even Rust or Golang). Cloud & Infrastructure Mastery: Deep experience with GCP cloud platform, containerization (Docker, Kubernetes), and modern CI/CD practices. Integration & Systems Design: Proven ability to architect REST/gRPC APIs, microservices, enterprise security integrations (SAML, OAuth, VPCs), and data pipelines. Client & Advisory Skills Executive Presence: Ability to switch effortlessly between white-boarding code with senior developers and presenting architectural strategies to CTOs and VP-level stakeholders. Technical Ownership: High autonomy, grit, and a strong sense of ownership: you don’t wait for answers; you invent solutions. Empathy & Communication: Exceptional written and verbal communication skills with a track record of building deep trust with client engineering teams. Nice-to-Haves Experience in specialized domains relevant to our tech stack (e.g., AI/ML infrastructure, distributed systems, high-throughput data processing, or cybersecurity). Prior experience in forward deployment, technical pre-sales, or high-touch technical account management at a high-growth SaaS or deep-tech enterprise company. Track record working within financial services, payments, or the broader FinTech ecosystem, with a solid understanding of the sector’s unique security, regulatory, and high-transaction requirements. Experience with other cloud platforms like Azure, AWS and Huawei. What Success Looks Like in Year 1 First 90 Days: Build deep technical trust with the customer’s core technical team, fully understand their tech stack and architecture, and ship your first production integration or PoC. 6 Months: Become the indispensable go-to technical expert for the account, reducing time-to-value for new client initiatives and driving architectural alignment. 1 Year: Expand the customer’s technical footprint with our solutions through successful PoCs, seamless system stability, and proactive feature delivery. Data Engineer We are seeking an experienced, energetic, and highly motivated Data Engineer to join our dynamic organisation. This role forms part of our Data and AI practice within our Data Engineering Team. You will be a lead part of a team of Data and AI practitioners delivering amazing technical solutions to our customers and our own business. This position demands a high level of expertise in Data Engineering technologies, particularly across the Google Cloud Platform (GCP) data stack and open-source big data ecosystems, a deep understanding of business contexts, and a strong motivation to innovate and lead. ADG is not a place for being still; this is an environment where you bring your energy and ideas, and we help you translate them into tangible solutions which drive real value. The successful candidate will be expected to deliver excellence across three core pillars: What we expect from you: Technical Mastery and Execution: At ADG we believe in mastery. We expect you to bring a wealth of experience to the table, specifically in architecting and building robust, scalable batch and real-time streaming pipelines. You must possess a deep understanding of cloud-native data ecosystems, open-source big data specifications, and distributed computing, while also staying at the forefront of GenAI technologies to solve complex, modern problems. Project Leadership and Delivery: You will take leading roles in project delivery, ensuring that technical solutions are successfully executed from concept to production. We expect you to drive accountability, manage complex technical timelines, and ensure high-quality outcomes that align with our clients’ strategic goals. Business Acumen and Initiative: At ADG, we are always improving. We expect you to go beyond the code to deeply understand the underlying business challenges our customers face and translate complex technical architectures into business value. If you see an opportunity for us to improve our services, architectures, or internal systems, speak up and take the initiative to drive that change. Mentorship and Skills Development: We believe in staying certified and ahead of the curve on technologies our customers use and want. This means we expect you to continuously refine your own skills, while also stepping up to mentor junior engineers, guide technical discussions, lead the development of Proof of Concepts (POCs), and elevate the overall capability of our Data practice. What you can expect from us: Technology Stack. At ADG we adapt to what our customers need. This coalesces around a robust set of data engineering technologies, with a heavy focus on the Google Cloud Platform (e.g., BigQuery, Cloud Dataflow, Cloud Storage, Pub/Sub, Cloud Dataproc, Cloud Composer) combined with core open-source big data specs (Apache Spark, Hadoop, Python, SQL) and an eye toward Generative AI frameworks. But we’re always learning more! A platform for impact. We provide a supportive environment that values your senior expertise from day one. You’ll be given the space and resources to architect innovative data solutions, lead complex projects, and have a direct, tangible impact on our customers’ success in a forward-deployed environment. A culture which values your journey. At ADG, we believe in autonomy, mastery, and purpose. We trust you to bring your best self to ADG and pursue continuous growth. We provide interesting and challenging work which assists that. We are a very collaborative organisation, which means you’ll find colleagues who support each other, brainstorm together, and build together. Requirements of this role: At least 7 years of proven industry experience in data engineering, data architecture, and enterprise software systems. A Computer Science (or equivalent) degree, or equivalent practical experience. Deep expertise in modern cloud architectures and GCP data engineering services (e.g., BigQuery, Cloud Dataflow, Cloud Storage, Pub/Sub, Cloud Dataproc, Cloud Composer, and Dataplex) for designing resilient batch and streaming pipelines. Exceptional, hands-on proficiency in core Data Engineering technologies, specifically Python, SQL, and Apache Spark, as well as key Data Management concepts. Deep understanding of diverse data architectures (e.g., open-source Big Data ecosystems, Hadoop, distributed computing, cloud-native databases, enterprise data lakehouses, and advanced analytics). A strong foundational grasp of both traditional data engineering paradigms and modern Generative AI (GenAI) technologies. Ai/Ml Engineer We are seeking an experienced, energetic, and highly motivated Senior AI/ML Engineer to join our dynamic organisation. This role forms part of our Data and AI practice within our Engineering Team. You will be a lead part of a team of Data and AI practitioners delivering amazing technical solutions to our customers and our own business. This position demands a high level of expertise in AI and Machine Learning technologies, a deep understanding of business contexts, and a strong motivation to innovate and lead. ADG is not a place for being still; this is an environment where you bring your energy and ideas, and we help you translate them into tangible solutions which drive real value. The successful candidate will be expected to deliver excellence across three core pillars: What we expect from you: Technical Mastery and Execution. At ADG we believe in mastery. We expect you to bring a wealth of experience to the table, specifically in architecting and building robust, scalable ML pipelines. You must possess a deep understanding of ML training methodologies, relevant algorithms, and evaluation metrics, while also staying at the forefront of GenAI technologies to solve complex, modern problems. Business Acumen and Initiative. At ADG, we are always improving. We expect you to go beyond the code to deeply understand the underlying business challenges our customers face and translate them into effective, measurable AI/ML solutions. If you see an opportunity for us to improve our services, architectures, or internal systems, speak up and take the initiative to drive that change. Mentorship and Skills Development. We believe in staying certified and ahead of the curve on technologies our customers use and want. This means we expect you to continuously refine your own skills, while also stepping up to mentor junior engineers, guide technical discussions, and elevate the overall capability of our Data and AI practice. What you can expect from us: Technology Stack. At ADG we adapt to what our customers need. This usually coalesces around a certain set of hyperscalers: Google Cloud, AWS, Azure, Oracle Cloud; and a robust set of modern ML technologies (e.g., Python, TensorFlow, PyTorch, and various GenAI frameworks/LLMs). But we’re always learning more! A platform for impact. We provide a supportive environment that values your senior expertise from day one. You’ll be given the space and resources to architect innovative solutions, lead complex projects, and have a direct, tangible impact on our customers’ success. A culture which values your journey. At ADG, we believe in autonomy, mastery, and purpose. We trust you to bring your best self to ADG and pursue continuous growth. We provide interesting and challenging work which assists that. We are a very collaborative organisation, which means you’ll find colleagues who support each other, brainstorm together, and build together. Requirements of this role: At least 7 years of proven industry experience in AI/ML engineering, data engineering and architectures. A Computer Science (or equivalent) degree, or significant proven industry experience. Proven, hands-on experience in designing, building, and deploying end-to-end ML pipelines into production environments. A deep and practical understanding of ML training processes, relevant machine learning algorithms (both classical and deep learning), and data preparation techniques. Strong knowledge of and practical experience with Generative AI (GenAI) technologies, LLMs, and related tooling. A go-getter attitude with a demonstrated ability to actively listen, understand complex business challenges, and design technical solutions that deliver ROI. Advanced proficiency in Python and solid experience with at least one major cloud provider (Google Cloud, AWS, or Azure). SDET / Test Engineer About the Role We are looking for a highly skilled SDET / Test Engineer to be the quality backbone for our software solutions. Someone who doesn’t just find bugs, but architects the automation frameworks and CI/CD gates that make quality first a reality across our client engagements. This isn’t a role where you write test cases and wait for a build. You will own test architecture end-to-end, write production-grade automation code alongside our engineers, and use AI tools to move faster from requirement to reliable, automated coverage. If you thrive at the intersection of deep technical testing skill, engineering rigor, and a relentless focus on system reliability, this role is for you. Key Responsibilities Test Architecture & Ownership: Design, build, and maintain scalable automation frameworks across UI, API, and integration layers, ensuring reliable, parallel, and fast-running test suites. Shift-Left Quality: Embed quality early in the SDLC; partnering with engineers during design and development, not just at the end of a sprint, to catch issues before they become expensive. CI/CD Integration: Build and maintain automated test pipelines (unit, integration, E2E, regression) that gate deployments and give the team confidence to ship continuously. Production-Level Contribution: Contribute real application code where needed, not just test code, understanding the system well enough to test it like an engineer who built it. Performance & Resilience Testing: Identify and test for bottlenecks under load, race conditions, and failure modes, especially for systems with strict uptime or regulatory requirements. AI-Accelerated Testing: Use AI tools to generate test scaffolding, analyse failures, identify coverage gaps, and speed up test maintenance while knowing where human judgment on risk and edge cases still has to lead. Cross-functional Collaboration: Work closely with engineering, product, and advisory teams to translate acceptance criteria into automated coverage, and to communicate risk and quality status clearly to non-technical stakeholders. What We’re Looking For Technical Expertise Automation Mastery: Strong hands-on experience with modern test automation tools (Playwright, Selenium, Cypress, or similar) and frameworks (TestNG, JUnit, Cucumber). Programming Proficiency: Solid coding ability in Java, TypeScript/JavaScript, Python, or similar and comfortable writing production-quality code, not just scripts. API & Data Testing: Proven experience validating REST APIs, JSON payloads, and structured data across complex, multi-system workflows. CI/CD & DevOps Fluency: Practical experience integrating automated testing into CI/CD pipelines (Jenkins, Azure DevOps, GitHub Actions, or similar) and working with version control (Git). Systems Thinking: Ability to reason about concurrency, state management, and data integrity in complex backend systems, not just click-through UI testing. Engineering & Communication Skills Engineering Mindset: You approach testing as an engineering discipline; designing for maintainability, scalability, and speed, not just coverage for its own sake. Ownership & Autonomy: High autonomy and grit; you identify quality risks proactively rather than waiting to be told what to test. Communication: Able to clearly explain technical risk and quality trade-offs to both engineers and non-technical stakeholders. Nice-to-Haves Experience in high-reliability, high-stakes domains; e-commerce, financial services, etc. Cloud platform experience (GCP, AWS, or Azure) and containerisation (Docker) for test environment management. Experience with performance/load testing tools (JMeter, k6, or similar) together with observability tooling. Exposure to AI-assisted test generation or self-healing test frameworks. Background contributing production code, not just test automation but also full-stack or backend development experience. What Success Looks Like in Year 1 First 90 Days: Understand our stack and client delivery model deeply; land your first meaningful automation framework improvement or CI/CD gate. 6 Months: Become the trusted quality authority across your project team, with automation coverage that catches real issues before they reach production. 1 Year: Drive measurable improvements in deployment confidence and speed through reusable frameworks, AI-accelerated test workflows across more than one client engagement. Full Stack Software Engineer About the Role We are looking for a deeply passionate, fast-learning Full-Stack Software Engineer to join our engineering team: designing, building, and deploying resilient, scalable web applications for our diverse client base. You will own the technical execution end-to-end; taking ambiguous client needs and turning them into robust, production-ready software across the full stack. If you’re not scared to use AI to accelerate your own work and ours, and you thrive on tackling ambiguity across different client ecosystems, this role is for you. Key Responsibilities Solution Design & Ownership: Independently design and implement scalable, production-ready applications; front-end, back-end APIs, and data storage, etc Technology Stack: Apply expert-level knowledge across modern JavaScript frameworks (React, Vue, Angular), microservices, cloud platforms (like GCP, AWS, OCI, or Azure), and performance-optimised databases. Quality & DevOps Champion: Establish best practices for clean code, comprehensive testing (unit, integration, E2E), security, and CI/CD, driving an always-shippable product. Customer-Centric Solutioning: Translate complex business requirements into simple, intuitive software experiences that clearly solve the problem. Strategic Reusability: Architect with modularity and componentisation in mind, building frameworks and patterns that can be rapidly tailored for new clients across sectors. Advanced Prototyping: Lead research and prototyping of complex features; real-time data integration, highly interactive UIs. AI-Accelerated Engineering: Use AI coding tools (e.g., Claude Code) to move faster; generating boilerplate, debugging, writing tests, and documentation while staying deliberate about where human review and judgment must take over. Cross-Functional Partnership: Collaborate closely with product, UX/UI, and business stakeholders to ensure successful technical definition and delivery of end-to-end solutions. Knowledge Sharing: Document technical designs, share best practices, and raise the engineering quality bar across the engineering team. What We’re Looking For Core Expertise Full-Stack Acumen: Expert-level proficiency in a modern front-end framework (React/ReactNative) and a back-end environment (Node.js/Express, Java Spring Boot, Python, etc.). Cloud & DevOps Mastery: Significant hands-on experience architecting and deploying on a major cloud platform (like GCP, AWS, OCI, or Azure), with proven CI/CD, monitoring, and containerisation (Docker) expertise. Data & Infrastructure: Hands-on expertise with relational and/or NoSQL databases; familiarity with serverless functions, application gateways, and networking. Infrastructure-as-Code (IaC); for example Terraform, experience is a plus. End-to-End Delivery: A track record of taking applications from concept through to live production, with an unwavering focus on reliability and performance. Problem-Solving & Communication Ownership & Ambiguity: Proven ability to take highly ambiguous business problems and translate them into well-defined, delivered technical solutions. Communication: Exceptional ability to explain complex architectural decisions to both technical and non-technical audiences. Team Player: Transparent and communicative, anticipating roadblocks and prioritising the team’s success over individual credit. Continuous Learning: A strong bias for fast, self-directed learning and staying current with new frameworks and best practices. Nice-to-Haves Data Engineering Skills: Experience with data pipelines, ETL/ELT processes, or working with large-scale/streaming data. AI Tooling & Workflows: Practical experience building AI-powered features (e.g., using the Claude API or similar), not just using AI as a coding assistant. Including prompt design, tool use, function calling, and evaluating model outputs in production. Experience across multiple cloud platforms (GCP, AWS, Azure, OCI). Experience contributing to reusable internal frameworks or libraries deployed across multiple clients. What Success Looks Like in Year 1 First 90 Days: Get up to speed on our stack and delivery model, ship your first production grade feature or integration for a client. 6 Months: Become a trusted technical anchor on your project team, contributing to architecture decisions and code review with confidence. 1 Year: Drive measurable improvements in delivery speed and quality through reusable patterns, AI-accelerated workflows, etc. Don't Keep Share!: WhatsApp Tweet