Role purpose
Convo needs a hands-on engineering Manager who will turn its full-stack team into an AI-native engineering organization. The role owns design, build and delivery of scalable, secure software, and its defining expectation is using AI agentic coding (autonomous and semi-autonomous coding agents, not just autocomplete assistants) to drive the whole development lifecycle.
The manager balances four things: technical execution, architecture, people management and delivery ownership. The candidate should have a strong engineering foundation in backend technologies such as Python and .NET, along with modern frontend frameworks such as React and Angular.
Key responsibilities;
AI agentic coding and AI-native engineering
- Make agentic coding a core part of the SDLC: agents handle requirements analysis, planning, design, code generation, debugging, refactoring, testing, documentation and code review.
- Build agent workflows: task decomposition, context engineering, repository instructions, structured prompts, tool integrations and multi-agent setups.
- Set human-in-the-loop (HITL) controls for reviewing, validating, security-checking and approving AI-generated code.
- Evaluate tools such as Cursor, Claude Code, GitHub Copilot and Codex, vendor-neutrally, and measure the productivity gains.
Full-stack engineering and technical leadership
- Lead end-to-end delivery across frontend, backend, APIs, databases and integrations.
- Backend: Python/.NET; frontend: React, Angular; cloud-native microservices and distributed systems.
- Stay hands-on in critical code, architecture reviews and complex problem-solving; set reusable patterns and coding standards.
Backend, APIs and platform
- Build versioned REST APIs and MCP servers that apps and AI agents can consume; define outbound contracts for data products, events and partner integrations.
- Own auth, identity, tenant isolation, API governance (versioning, schema validation, rate limits), and usage/token metering with quotas and audit trails.
- Design async, event-driven service communication, caching and database performance.
Frontend engineering
- Set frontend architecture, component libraries, state management and API integration patterns.
- Embed AI features (agent interfaces, conversational UX, workflow automation) while keeping UX, performance and accessibility consistent.
Delivery, quality, security and team leadership
- Turn product requirements into plans, sprints and milestones; manage capacity, CI/CD, releases and technical debt.
- Hold AI-generated code to the same production, security and quality bar as hand-written code.
- Drive automated testing (unit, integration, contract, regression, security), observability and documentation.
- Hire, mentor and grow a high-performing team; report progress, risks and productivity to the Head of Engineering.
Requirements
- 10+ years in software engineering and technical delivery, including 4+ years leading frontend, backend and QA teams.
- Proven hands-on use of AI coding agents (Cursor, Claude Code, GitHub Copilot, Codex) to independently deliver complete features, APIs, UI components and tests.
- Backend expertise in Python/FastAPI or .NET/C#, and frontend expertise in React or Angular.
- Solid knowledge of REST APIs, microservices, distributed systems, SQL/NoSQL databases, MCP servers and AI agent integrations.
- Cloud and DevOps experience: Azure, AWS or SAP BTP; Docker, Kubernetes, CI/CD, Git workflows and observability.
- Ability to turn business requirements into technical plans and manage timelines, resources, risks and stakeholders.
- Excellent written and spoken English, with strong client-facing communication: able to understand client needs, propose better solutions and persuade clients to adopt them
