Backend Lead - Hands-on Tech Lead

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 implementa