[Hiring] Senior Engineering Manager @Nerdio

Role Description

We are looking for a Senior Engineering Manager to lead a growing AI-native R&D team of 10+ engineers. This dual-track role combines direct people management with hands-on coding, architecture, and technical execution. You will remain close to the work, establish responsible AI-assisted development practices, and earn technical trust by helping solve the group’s most difficult engineering problems.

You will own the technical execution of complex problems from initial concept through implementation, evaluation, product validation, and production readiness. You will use AI coding agents and agentic frameworks as part of your daily workflow and help the team do the same without sacrificing code quality, security, reliability, or architectural discipline. You will turn ambiguous needs into clear, testable specifications, measurable evaluation criteria, and executable engineering backlogs, then ensure validated concepts are production-ready or transferred to product engineering through clear documentation and structured handoffs.

Qualifications

• 7+ years of professional software engineering experience, including ownership of complex systems from design through production.
• 4+ years of engineering management experience with direct responsibility for coaching, performance management, hiring, career development, and team health.
• Demonstrated success leading an engineering team of comparable size while remaining hands-on with prototypes, incubation code, architecture, critical technical reviews, and the productionization of validated concepts.
• Strong software engineering fundamentals across backend development, distributed systems, system design, API design, testing, and clean code.
• Hands-on experience using AI coding assistants, coding agents, and agentic workflows in real software delivery work, not only demonstrations or personal experiments.
• Strong proficiency in C#/.NET, or comparable backend expertise with the ability to become productive quickly in C#, plus experience integrating LLM APIs into applications or engineering workflows.
• Experience with a major cloud platform such as Microsoft Azure, AWS, or Google Cloud, containerized development with Docker, and container orchestration technologies such as Kubernetes.
• Practical knowledge of observability, including structured logging, metrics, tracing, monitoring, alerting, and evaluation of AI-powered features.
• Ability to review AI-generated code critically for correctness, security, maintainability, testing gaps, and architectural fit.
• Working knowledge of responsible AI-assisted engineering practices, including source-code and data-handling boundaries, human review, testing, traceability, and secure use of approved tools.
• Excellent written and verbal communication, sound technical judgment, and comfort turning ambiguity into decisions and executable plans.

Requirements

• Own R&D initiatives end to end.
• Take ideas through specification, technical design, implementation, testing, evaluation, product validation, documentation, production readiness, and a structured handoff to product engineering with a high degree of independence and accountability.
• Build with AI in the loop.
• Turn vague needs into executable specifications.
• Develop the team’s AI engineering capabilities.
• Set and uphold a high engineering bar.
• Make sound architectural decisions.
• Measure and improve the workflow.
• Partner across functions.

Benefits

• Competitive Base and Incentive Plan
• Stock Options
• Health and Welfare Plans*
• Life and Disability Plans*
• Retirement Plan*
• Unlimited Flexible Paid Time Off, including your birthday off!
• Collaborative Team Culture

* Benefits for international employees, outside the US, vary by country.