Associate Engineering Manager

As an Associate Engineering Manager on the AI Platform team, you will balance technical depth with people leadership. You will guide a growing team of engineers, drive delivery on foundational AI infrastructure, and stay connected to the codebase through architecture reviews, technical guidance, and hands-on contributions. You bring 2–4 years of management experience paired with a strong foundation as a practitioner who has shipped production code. Job Responsibilities

People Leadership

• Manage, mentor, and grow a team of 6+ engineers across varying experience levels, fostering a culture of ownership, psychological safety, and continuous improvement. - Conduct regular 1:1s, performance reviews, and career development conversations to support individual growth aligned with team and company goals. - Actively participate in recruiting and hiring, including contributing to the current open engineering role on the team. - Identify skill gaps on the team and partner with senior leadership and HR to develop targeted growth plans or address hiring needs. Technical Oversight & Delivery

• Own the delivery roadmap for the AI Platform team, partnering with Product and senior engineering leadership to plan, prioritize, and execute milestones. - Participate in architecture and design reviews for AI API infrastructure, LLM call management, streaming, history storage, and cost tracking systems. - Provide technical guidance and review for the Agent framework, with a focus on security, scalability, and reliability – including agent execution data and cost telemetry. - Perform code reviews and uphold high engineering quality standards across the full stack. - Stay technically engaged with the codebase, contributing code where appropriate to unblock the team or lead by example. - Identify and mitigate technical risks and drive resolution of production incidents in partnership with your team. Cross-Functional Collaboration

• Work closely with downstream product teams who consume the AI APIs, understanding their needs, and translating them into clear technical requirements for your team. - Collaborate with security, infrastructure, and data teams to ensure the Agent framework and LLM infrastructure meet enterprise-grade standards. - Communicate progress, risks, and tradeoffs clearly to both technical and non-technical stakeholders. - Contribute to the broader engineering culture at SmartBear through participation in cross-team initiatives, engineering standards, and knowledge sharing. Skills Required

Management & Leadership

• 2–4 years of engineering management experience, with a track record of leading teams that have shipped production software. - Demonstrated ability to coach and develop engineers at varying levels, including navigating performance conversations and building growth plans. - Experience hiring engineers, including sourcing, interviewing, and onboarding. - Strong written and verbal communication skills; able to tailor technical discussions to both engineering audiences and business stakeholders. Technical Skills

• Hands-on background as a software engineer with prior experience writing and shipping production code; comfortable reading code, contributing to reviews, and engaging deeply in architecture discussions. - Proficiency in TypeScript and/or Python

• Understanding LLM-based architectures and AI/Agent-based systems (e.g., LangChain, LangGraph, or comparable frameworks); hands-on experience is a strong plus. - Familiarity with API design and management, including RESTful services and modern API concepts such as MCP (Model Context Protocol). - Experience with cloud infrastructure on AWS and containerized deployments using Docker; able to reason for scalability and reliability tradeoffs. - Understanding security principles as they apply to AI systems, including secure credential management, access control, and data handling for multi-tenant environments. - Familiarity with observability practices: logging, monitoring, alerting, and cost tracking in production of AI systems. - Experience with NoSQL or vector databases is a plus. Ways of Working

• Able to operate with ambiguity, define structure, and drive clarity for the team when requirements are evolving. - Data-informed mindset – measures outcomes, iterates on processes, and uses metrics to guide both engineering and team health decisions. - Comfortable balancing competing priorities across people, product delivery, and technical quality simultaneously. - Collaborative and low-ego; builds trust quickly with peers, reports, and senior leadership alike. Why you should join the SmartBear crew:

• You can grow your career at every level. - We invest in your success as well as the spaces where our teams come together to work, collaborate, and have fun. - We love celebrating our SmartBears; we even encourage our crew to take their birthdays off. - We are guided by a People and Culture organization - an important distinction for us. We think about our team holistically – the whole person. - We celebrate our differences in experiences, viewpoints, and identities because we know it leads to better outcomes. Did you know:

• Our main goal at SmartBear is to make our technology-driven world a better place. - SmartBear is committed to ethical corporate practices and social responsibility, promoting good in all the communities we serve. - SmartBear is headquartered in Somerville, MA with offices across the world including Galway Ireland, Bath, UK, Wroclaw, Poland, Ahmedabad and Bangalore India. - We’ve won major industry (product and company) awards including B2B Innovators Award, Content Marketing Association, IntellyX Digital Innovator and Built-in Best Places to Work. SmartBear is committed to creating an inclusive workplace for employees where all individuals are treated with respect and dignity. We are dedicated to fostering a workplace that reflects a diversity of thought and experience as well as our values of being smart, open, driven, accountable, and curious. #LI-AC2