Engineering Lead

Job Description: Engineering Lead

Experience: 7-9 years

Team: 5-6 developers and QA engineers

About the role

You own the technical side of the product from end to end. You design the architecture, lead the team and translate business requirements into technical plans. When necessary, you also write the code yourself.

What you will do

• Design the system architecture and make the main technical decisions.

• Lead a team of 5-6 developers and QA engineers. Plan the work, review it and help each person grow.

• Work closely with product, marketing and leadership.

• Translate business requirements into clear technical plans and timelines.

• Own all cost decisions: cloud, infrastructure, tools and vendors.

• Keep the application stable in production. Know how each part of the system works.

• Write code, review pull requests and solve difficult problems when the team needs help.

Core knowledge

• System architecture

• Computer networks (DNS, HTTP, TLS, CDNs, latency)

• Database design

• API design

• Applied AI: build product features with LLMs, not only use AI tools to write code

• Data privacy and global compliance (GDPR and similar laws). We will need this as we grow.

What we look for

• 7-9 years in software engineering, with a minimum of 2 years as a tech lead or engineering manager.

• Experience with cloud platforms and live production systems.

• An AI-native work style: you use AI tools (Claude Code, Cursor, Copilot) every day and help your team use them well.

• Clear communication with both technical and non-technical people.

• Good judgement on the cost and business impact of each technical decision.

• Comfort in a small, fast-paced team with high ownership.

AI-Native Engineering Mindset

We value engineers who actively use AI to improve how software is built and delivered. The ideal candidate:

• Uses AI coding assistants such as Claude Code, Cursor, or GitHub Copilot as part of their daily workflow.
• Understands the strengths and limitations of AI-generated code and can validate its correctness, security, and maintainability.
• Has hands-on experience integrating LLMs into real product workflows, rather than limiting AI usage to code generation.
• Can guide the team in adopting AI tools responsibly and measuring their impact on engineering productivity.

Tech Stack

• Programming Language: TypeScript
• Database: PostgreSQL
• Backend & Platform Services: Supabase, Firebase
• Infrastructure & Edge Network: Cloudflare