Backend Lead - Hands-on Tech Lead

Job description

Job Description International fast-growing IT company StellarTech is looking for a Backend Lead - Hands-on Tech Lead / Player-Coach. StellarTech is a fast-growing international product technology company looking for a Backend Lead to own the technical direction, engineering quality, and operational health of our backend ecosystem. This is a hands-on player-coach role combining backend architecture, technical execution, engineering leadership, and people management. You will lead a small team of experienced backend engineers while remaining actively involved in technical design, critical implementation, code reviews, production troubleshooting, and technical research. You will work in a cross-functional product environment and take responsibility not only for backend implementation, but also for product delivery, reliability, and long-term technical sustainability. What You’ll Do: Own the backend technical direction and architecture across our product ecosystem. Translate product initiatives into technical solutions: clarify requirements, assess feasibility, identify risks, prepare technical designs, and decompose work for the team. Own the complete engineering lifecycle from refinement and solution design to implementation, release, monitoring, and production improvements. Design scalable, reliable, and maintainable backend solutions aligned with product and business needs. Build and evolve shared backend capabilities, reusable components, and platform solutions that allow the company to launch and scale multiple products efficiently. Define service boundaries, data ownership, APIs, integration patterns, and communication between systems. Make and defend pragmatic architectural decisions, including: Monolith vs services. Synchronous vs asynchronous communication. SQL vs NoSQL. Build vs buy. Short-term delivery vs long-term technical sustainability. Remain hands-on with Python and FastAPI through critical implementation, prototyping, debugging, code reviews, and technical research. Lead the design of event-driven and asynchronous workflows, including retries, idempotency, ordering, failure handling, and message processing. Own backend production readiness and operational health, including monitoring, logging, alerting, dashboards, SLIs/SLOs, runbooks, incident response, root-cause analysis, and post-incident improvements. Establish clear ownership of backend services and ensure the team can support them without dependency on individual engineers. Improve engineering practices covering refinement, technical design, Definition of Done, testing, code review, CI/CD, release safety, documentation, and technical debt management. Introduce and scale AI-assisted and agentic development workflows across the backend team. Evaluate how AI tools affect delivery speed, engineering quality, maintainability, and team productivity. Lead and develop backend engineers through delegation, regular feedback, one-to-one meetings, mentoring, performance reviews, and career development. Collaborate closely with Product, Platform, DevOps, QA, Frontend, and other engineering leads. Take responsibility for product and business outcomes, not only technical implementation. What We’re Looking For: 7+ years of backend engineering experience. 2+ years of experience in a Tech Lead, Team Lead, or Backend Lead role. Strong and recent hands-on production experience with Python, ideally 5+ years. Strong knowledge of modern Python backend development practices. Production experience with FastAPI or similar Python web frameworks. Experience with asynchronous programming, testing, typing, profiling, debugging, and maintainable application design. Proven experience owning backend architecture end to end, not only contributing to solutions designed by others. Experience making and defending architectural decisions with Product, Engineering, and business stakeholders. Experience building and operating scalable, high-load, or data-intensive production systems. Strong understanding of service design, system boundaries, data flows, integrations, and distributed system trade-offs. Strong experience with event-driven systems, asynchronous processing, and message brokers such as Kafka, RabbitMQ, SQS, or similar. Good understanding of retries, idempotency, message ordering, delivery guarantees, dead-letter handling, and failure recovery. Strong database fundamentals, including: Data modelling. Transactions and isolation. Indexing. Locking and concurrency. Query plans. Performance diagnosis and optimisation. Production experience with MongoDB and an understanding of its modelling, consistency, and scaling trade-offs. Production experience with relational databases, preferably PostgreSQL. Experience designing APIs and integrating external platforms, third-party services, and payment or subscription systems. Strong production ownership mindset, including monitoring, alerting, debugging, incident investigation, and reliability improvements. Experience with cloud infrastructure, containerised applications, deployment tooling, and CI/CD. Ability to reason about deployment safety, rollbacks, scalability, resource limits, and system capacity. Proven experience improving an engineering process, technical area, or system from an unclear or immature state to a measurable target state. Ability to balance product delivery speed with architecture quality and long-term maintainability. Experience leading experienced engineers without micromanagement. Experience with delegation, performance feedback, team development, and technical ownership distribution. Strong ownership, initiative, structured communication, and ability to make decisions under uncertainty. AI-First Engineering Experience: We are looking for more than occasional chatbot usage or basic code generation. A strong candidate should be able to provide concrete examples of using AI in an end-to-end software delivery workflow, such as: Spec-driven or context-driven development. AI coding agents. Automated code review. Test and documentation generation. Reusable repository or company-level AI context. Agentic pipelines and workflow automation. AI-assisted debugging and incident investigation. Evaluations and quality gates. Security and data privacy controls. Measuring the impact of AI adoption on delivery speed and quality. Introducing AI workflows across an engineering team. Nice to Have: Experience building multi-product, multi-tenant, or platform-based architectures. Experience creating internal frameworks, service templates, or reusable backend components. Experience scaling products without proportional growth of the engineering team. Experience with AWS, including S3, Lambda, ECS, EKS, or related services. Experience with Redis. Hands-on Kubernetes experience. Strong Docker experience. Experience with GitHub Actions or similar CI/CD tooling. Experience with Temporal or another workflow orchestration platform. Experience applying DDD, CQRS, event sourcing, or similar architectural patterns pragmatically. Experience with B2C, EdTech, subscriptions, payments, analytics, or mobile-first products Experience working in an early-stage or fast-changing product environment. Good Fit for This Role: This role is a good fit for someone who: Remains a strong hands-on backend engineer. Enjoys combining coding, architecture, and leadership. Can independently assess the current technical state and define a better target state. Creates engineering processes rather than only following existing ones. Takes ownership of services after they are released to production. Can make pragmatic architectural decisions without unnecessary complexity. Thinks about product and business outcomes, not only implementation. Can set a technical standard for experienced engineers. Is comfortable challenging existing decisions and defending a well-reasoned position. Sees AI as a way to redesign engineering workflows, not only generate code. Is ready to lead both technology and people. Why You’ll Love Working With Us: Innovative environment: We are building and scaling EdTech products while actively experimenting with new technologies and development approaches. Global remote work: Work with an international team from anywhere within a compatible time zone. Health support : Company-provided medical expense compensation. AI tools : Company-provided AI subscriptions and other engineering tools. Flexible time off : 21 days of annual leave plus 10 bank holidays. Collaborative culture: Work alongside experienced and motivated professionals who value ownership, speed, and measurable results. Real influence: Help define the backend strategy, engineering standards, and AI-first development practices of a growing product ecosystem. Interview Process: HR interview Technical Interview Leadership Interview Final interview