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
Originally posted on