Quick overview
Job description
This is a player-coach role. You'll lead a small team of engineers and technical leads, give technical direction to offshore engineering teams through a dotted-line relationship, and own the design of the systems your team builds. You'll stay close to the code through design and code reviews, proofs of concept, and troubleshooting, and you'll be accountable for high-quality releases and customer deployments.
What You'll Be Doing
- Lead, mentor, and develop a small team of engineers and technical leads, and give technical direction to offshore teams through a dotted-line relationship.
- Design and own the architecture of complex, distributed, real-time systems, including integrations, APIs, scalability, reliability, and security.
- Run design and code reviews and keep engineering standards high for quality, testing, and maintainability.
- Drive AI-driven software development across the team, using AI coding assistants and agents for design, coding, testing, code review, and defect resolution, with clear quality and security guardrails.
- Stay hands-on: build proofs of concept, troubleshoot production and implementation issues, and write code when needed.
- Own delivery of product releases and customer deployments, working with Product Management, Architecture, QA, DevOps, and Professional Services.
- Evaluate AI and contact center technologies and integration approaches across CCaaS and AI platforms.
What You'll Bring to the Role
- 8+ years of software engineering experience, including 3+ years of engineering management while staying hands-on.
- Proven experience designing and building complex distributed systems, such as event-driven, low-latency, cloud-native, and real-time integrations.
- Hands-on JavaScript, TypeScript, and Node.js experience, recent enough to review code and build proofs of concept.
- Daily, practical use of AI-assisted development tools such as GitHub Copilot, Cursor, Claude Code, or similar, and experience helping a team adopt them.
- Working knowledge of AI technologies such as LLMs, RAG, agents, and prompt and evaluation practices.
- Experience with cloud platforms (Google Cloud preferred; AWS or Azure also considered) and Kubernetes.
- Strong practices in code review, CI/CD, and Agile delivery, with a track record of shipping on committed timelines.
- Experience with Google AI technologies (Vertex AI, Gemini, CCAI) or with AWS Bedrock, Azure AI, OpenAI, or Anthropic.
- Experience with contact center platforms such as Genesys Cloud, Amazon Connect, NICE CXone, or Cisco.
- Experience leading distributed or offshore engineering teams.
- Experience in SaaS product organizations or startup-style environments.
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