We're building a small, exceptional engineering team of 10-12 people who want to do the best work of their careers. Our culture is built on a few non-negotiables: AI-native from day one. We use Cursor, Claude Code, Codex, and actively incorporate new tools and workflows as we find ones that work. We prioritise a productive SDLC that strikes the right balance between stability and experimentation, using AI to raise quality and eliminate drudgery. Ownership over outcomes. Engineers here work directly with clients, understand the business problem, and own the solution end to end. No ticket factories. Flat, low-ego, high-trust. Good ideas win regardless of who has them. We lead by example, not by title. No management ladder, just smart people solving hard problems together. Stack agnostic. We use whatever lets us ship great work that clients love. No dogma. Meaningful upside. The people who build SoundsenseAI should share in what it becomes. Equity and performance bonuses for those who stay and help us grow. We work in small squads of 1-3 engineers, collaborating closely with our UK team and clients. Continuous learning is built into how we work, not bolted on as an afterthought. And we get together in person periodically, both within the SA team and with UK colleagues, to build real relationships. Who We're Looking For Systems thinkers. Product-minded engineers. People who care about solving the right problem, not just writing clean code. Engineers who think commercially and want to understand the business before they touch the stack. Curious experimenters who try new tools, find what works, and bring it back to the team. Engineering is evolving toward consulting and product thinking, and this is a place where that evolution is already happening. Based in South Africa. Remote-first. Building something that matters.

We run a structured, lightweight process so you always know what to expect. The goal is to assess three things: Your technical depth and ability to ship. Your ability to operate in a client-facing consulting environment. Whether Soundsense is the right place for you. Typical timeline is around 2 weeks from first call to decision. Note: Stages and timings may vary slightly by role, but we will always tell you what’s changing and why. Stage 1: Intro & Alignment (45–60 mins) Who you’ll meet: Founder What we cover Your background and what you want next. Why Soundsense, and why this role. How you like to work day-to-day in a remote setup. A quick practical check that you actively use modern AI-assisted engineering tools in real projects. What you can expect A conversation, not a quiz. Time for your questions about the role, clients, and how we operate. Stage 2: Culture & Ways of Working (60 mins) Who you’ll meet: Other founder What we cover How you make trade-offs between speed, quality, and maintainability. How you take ambiguous problems and create momentum. Communication and feedback style. Working effectively in a remote, high-autonomy environment. Stage 3: Technical Deep Dive (90–120 mins) Who you’ll meet: Senior engineer + founder What we cover Requirements discovery, architecture, and pragmatic delivery. LLM engineering fundamentals Security, observability, and operational concerns. Format This is usually split into a few short segments, for example: Discovery + architecture role-play (you ask questions, then propose a solution). LLM engineering discussion (how you would design for robustness, governance, and edge cases). Code review / production critique (identify risks and propose improvements). References / code sample For some roles we will ask for one or two of the following: A short code sample (GitHub repo or a sanitized excerpt). A brief write-up of a system you’ve built. References from a previous employer If this is required, we will tell you in advance and keep it lightweight. Decision & Offer We aim to give a clear outcome quickly. If it’s a yes, we will move to references (if relevant) and discuss contract details, start date, and expectations. If it’s a no, we will be direct and respectful. When possible, we will share brief feedback. Your questions Please bring questions at every stage. We want you to evaluate us as much as we evaluate you.

Location: Remote-first (preference for Cape Town)Contract Length: 6 months (but looking to extend if good fit)Commitments: 4-5 days a week (flexible)Rate: Competitive day rate We are seeking a Lead Software Engineer with passion for AI to architect, build, and deploy custom AI solutions for key clients. You will work closely with client teams to transform complex operational challenges into production-ready systems with rapid, measurable impact. What Makes This Role Unique You will join a high-caliber team of engineers building production AI for diverse needs. This is a hands-on role where you define the architecture and watch over the AI that is writing the code. High-Level Ownership: Influence client outcomes and internal product direction. Complex Impact: Solve high-stakes operational challenges using SOTA AI. AI-Native Transformation: Work at the strategic frontier, redesigning businesses to be AI-native rather than just layering AI onto legacy processes. Empowered Culture: Remote-first environment built on trust, autonomy, and a shared commitment to engineering excellence. Experienced Founders: Learn from a team who have built and sold businesses. Build Vertical Experience: Build a deep understanding of various business domains that will make you valuable in the job market See who you would be working with Example Projects You'd Work On Build an AI to analyse laboratory results, extract and translate the data to a standardised format alongside concluding commentary on the results Build an AI to summarise the state of a customer account for a car finance business (calls, emails, payments, loan details, previous CRM actions etc) to understand current state and give the next best action to maximise recovery processes Build an AI to automatically book or reschedule a engineering appointments for building maintenance services Who Is This Role For? The Pragmatic Architect: Translates ambiguous business needs into lean, production AI. The High-Velocity Builder: Prioritizes shipping working solutions over technical perfection. The Technical Consultant: Acts as a strategic bridge between stakeholders and code. The Agentic Developer: Multiplies output using AI coding tools without sacrificing quality. The Autonomous Leader: Thrives in low-direction environments where you own the quality, timeline, and value of the final product. Core Responsibilities Scoping: Translate complex business problems into technical AI roadmaps. Development: Architect and build full-stack AI applications from data to UI. Deployment: Launch SOTA models into production (cloud, on-prem, or hybrid). Enablement: Lead workshops and document solutions for successful client handovers. Collaboration: Partner with internal R&D to influence the core technology roadmap. Optimization: Monitor and tune systems to ensure continuous value and meet KPIs. Leadership: Lead a pod of 2-3 engineers in a low friction environment About You 🎯 Key Requirements Experience: 6+ years shipping at scale. Expert at balancing speed, scalability, and complexity based on project stage and domain. Full-Stack: Expert in React, TypeScript, API design, containerization, and cloud (AWS/GCP/Azure). Velocity: Strong "ship fast" mentality with end-to-end ownership of outcomes. LLM Engineering: Expert at implementing RAG, robust evaluation systems, and LLM data processing pipelines using either existing frameworks or homegrown solutions. Agentic Coding: Has leveraged AI coding agents to accelerate delivery while ensuring rigorous development standards, robust testing, and seamless collaboration within a shared codebase. Product Sense: Intuitive UX grasp, iterates quickly to a "good enough" production state. Leadership: Sets best practices for others and drives quality within small, agile teams. Strategic Communication: Excels at technical discovery and managing client expectations. ✨ Bonus Points Strategic Growth: Ambition to provide technical oversight across multiple projects and squads. DevOps: You can have experience managing servers and services to ensure that solutions run on the client site Vertical Expertise: AI experience in specialized industries like Finance, Healthcare, or Field Services. Niche AI: Expertise in multi-modal LLMs, voice processing, or edge deployment. Entrepreneurial: Background as a founder or early employee at a seed-stage startup. ❌ This Role Is NOT For Junior Developers seeking on-the-job training. Engineers who prefer minimal client interaction. Individuals requiring constant direction or detailed task specifications. Perfectionists who prioritize technical elegance over building solutions that add value. Apply

Location: RemoteJob Type: Contract We are seeking a highly skilled and experienced contract data scientist to lead the development of a cutting-edge AI prioritisation model for a debt collections process. This critical role involves transforming our collections process into a data-driven, strategic operation by intelligently prioritising daily arrears worklists, ultimately empowering our agents, improving cash flow, and reducing arrears. What Makes This Role Unique: You’ll be joining a small, senior team working directly with an experienced and hands-on CTO and product leader. We move fast, operate lean, and collaborate closely. You’ll have a lot of autonomy, the chance to work on meaty problems, and be directly involved in shaping real product decisions. This is high-impact work with real-world consequences — helping SMEs, many of whom are still miles behind on AI adoption, make a leap forward. Core Responsibilities: Build, train, and validate a machine learning model using historical data to ensure predictive accuracy. Collaborate with technical teams to define and build the data exchange process, including developing a production API to deliver the prioritised worklist. Deploy the backend scoring engine into a secure production environment, addressing data residency and regulatory requirements. Implement robust monitoring and reporting to track model performance, prevent silent failures, and ensure outputs are based on the freshest available data. Analyze the performance of the live system against defined KPIs and synthesise findings into a final report. Provide data-driven recommendations and a clear strategic pathway for the next version of the solution. Required Skills: Proven experience in developing, training, and validating machine learning models. Expertise in data discovery and data flow design. Skilled in constructing data engineering pipelines. Proficiency in implementing monitoring and reporting to track model performance. Experience in analysing KPI data and contributing to strategic roadmaps. Experience in collaborative design of solution architecture and API specifications. Strong communication skills to work effectively with both technical and business teams during workshops, testing, and go-live phases. Work Terms: Project Length: 16 weeks Weekly Commitment: 4 days Rate: Competitive daily rate Location: Remote/On-site flexibility Apply