Engineering Manager

Convo is seeking an experienced Engineering Manager to lead its full-stack team in becoming an AI-native engineering organization. This hands-on role involves owning the design, development, and delivery of scalable, secure software solutions with a strong emphasis on AI agentic coding—leveraging autonomous and semi-autonomous coding agents throughout the entire development lifecycle. The ideal candidate will expertly balance technical execution, architectural vision, people management, and delivery ownership. A solid engineering background in backend technologies such as Python and .NET, alongside modern frontend frameworks like React and Angular, is essential.

Key Responsibilities

AI Agentic Coding and AI-Native Engineering
- Integrate agentic coding deeply into the software development lifecycle, enabling AI agents to manage requirements analysis, planning, design, code generation, debugging, refactoring, testing, documentation, and code review.
- Develop and optimize agent workflows involving task decomposition, context engineering, repository instructions, structured prompts, tool integrations, and multi-agent coordination.
- Implement human-in-the-loop (HITL) controls to review, validate, secure, and approve AI-generated code.
- Conduct unbiased evaluations of AI coding tools such as Cursor, Claude Code, GitHub Copilot, and Codex, measuring productivity improvements and effectiveness.

Full-Stack Engineering and Technical Leadership
- Lead end-to-end delivery across frontend, backend, APIs, databases, and integrations, ensuring seamless collaboration and high-quality output.
- Maintain hands-on involvement in critical code contributions, architecture reviews, and complex problem-solving, while establishing reusable patterns and coding standards.
- Drive backend development using Python and .NET, frontend development with React and Angular, and design cloud-native microservices and distributed systems.

Backend, APIs, and Platform
- Build versioned REST APIs and MCP servers that support consumption by applications and AI agents; define outbound contracts for data products, event streams, and partner integrations.
- Own authentication, identity management, tenant isolation, API governance (including versioning, schema validation, rate limiting), and usage/token metering with quotas and audit trails.
- Architect asynchronous, event-driven service communication, caching strategies, and database performance optimization.

Frontend Engineering
- Define frontend architecture, component libraries, state management, and API integration patterns.
- Embed AI-driven features such as agent interfaces, conversational user experiences, and workflow automation, while maintaining consistent UX, performance, and accessibility standards.

Delivery, Quality, Security, and Team Leadership
- Translate product requirements into actionable plans, sprints, and milestones; manage team capacity, CI/CD pipelines, releases, and technical debt.
- Ensure AI-generated code meets the same production, security, and quality standards as hand-written code.
- Promote automated testing practices including unit, integration, contract, regression, and security tests, alongside observability and comprehensive documentation.
- Hire, mentor, and develop a high-performing engineering team; regularly report progress, risks, and productivity to the Head of Engineering.

Required Qualifications
- Over 10 years of experience in software engineering and technical delivery, with at least 4 years leading frontend, backend, and QA teams.
- Demonstrated hands-on expertise using AI coding agents (such as Cursor, Claude Code, GitHub Copilot, Codex) to independently deliver complete features, APIs, UI components, and tests.
- Strong backend proficiency in Python/FastAPI or .NET/C#, and frontend expertise in React or Angular.
- Deep understanding of REST APIs, microservices, distributed systems, SQL/NoSQL databases, MCP servers, and AI agent integrations.
- Experience with cloud platforms and DevOps tools including Azure, AWS, or SAP BTP; Docker, Kubernetes, CI/CD pipelines, Git workflows, and observability tools.
- Proven ability to translate business requirements into technical plans, managing timelines, resources, risks, and stakeholder expectations.
- Excellent written and spoken English communication skills, with strong client-facing abilities to understand needs, propose improved solutions, and influence adoption.

This role offers a unique opportunity to shape the future of AI-driven software development within a dynamic and innovative environment. Candidates passionate about pioneering AI-native engineering practices and leading talented teams are encouraged to apply.