Lead Software Engineer

Role Summary: 

As our Lead Full Stack Software Engineer, you will own the future of how OfficeSpace builds, hosts, monitors, and deploys AI features, from Chatbots to Customer facing MCP Servers to Autonymous agents that handle day to day facilities management tasks. 

We move fast. We expect precision. And we trust you to own outcomes. 

What You’ll Do: 

• Lead the architecture and production evolution of OfficeSpace’s AI platform. 

• Design and operate Python-based AI services that integrate deeply with our Ruby on Rails backend and React frontend. 

• Partner with our Devops team to define best practices for deploying and hosting AI agents 

• Act as the technical owner for AI reliability—defining guardrails, observability, testing strategies, and failure modes for AI-driven functionality. 

• Build and evolve full-stack systems with a long-term mindset—maintainable code, extensible architectures, and clean interfaces. 

• Define and drive performance benchmarks across AI systems, using metrics, profiling, and load testing to improve latency, throughput, and stability. 

• Design and operate cloud-native, data-intensive systems using GCP, BigQuery, and Kafka to power event-driven and AI-enabled workflows. 

• Embed quality early—shift-left testing, observability, and validation to ensure predictable, enterprise-ready releases. 

• Proactively address security, data integrity, and technical debt—especially where AI intersects with customer data and core workflows. 

• Partner with senior engineers and architects to evaluate designs, align on tradeoffs, and move the system forward. 

• Mentor engineers through thoughtful code reviews and technical guidance, with room to step into formal people leadership over time. 

What You Bring: 

• 7+ years building and evolving production web applications, with demonstrated ownership of complex systems and technical direction. 

• Strong backend experience (Python or Ruby on Rails preferred; Java, Node.js, or Go welcome) and modern frontend development (React preferred). 

• Hands-on experience shipping AI-driven features in production—LLM-based systems, automation workflows, or agentic patterns—with an emphasis on safety, observability, and maintainability. 

• Deep understanding of cloud-native systems (GCP preferred), data platforms (BigQuery), and event-driven architectures (Kafka). 

• Proven ability to design for enterprise-scale performance, reliability, and security. 

• Comfort operating as a technical leader—navigating differing opinions, driving alignment, and mentoring peers. 

• A builder’s mindset. You move with urgency, think long-term, and take ownership from idea to impact. 

• An early adopter’s curiosity for agentic AI—and the discipline to ship it responsibly.