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Engineering Team Lead, Appointment Scheduling

Engageware
Posted a day ago, valid for 22 days
Location

Boston, MA, US

Salary

Competitive

Contract type

Full Time

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Sonic Summary

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  • Engageware is seeking a hands-on Team Lead for their Appointment Scheduling team, which manages millions of appointments daily for major banks and healthcare systems.
  • The ideal candidate should have a proven track record of leading engineering teams and delivering products, with experience in JVM backend technologies and modern TypeScript front ends.
  • Candidates must also have experience in modernizing business-critical systems and fluency with AI-augmented development methodologies.
  • This role requires a genuine product sense and a focus on enhancing the customer booking experience, along with a willingness to travel occasionally within the United States.
  • The position offers a competitive salary of $150,000 to $180,000, with a requirement of at least 5 years of relevant experience.

About the Role

Engageware powers appointment scheduling for some of the largest banks, credit unions, healthcare systems, and retailers in the world — on the order of a million appointments and interactions a day. When someone books time with their bank or schedules a visit with their care team, our platform finds the right availability, the right person, and the right place, and makes it effortless: online, in the branch, at the kiosk, in the walk-in queue, or virtually, with reminders and routing handled end to end.

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We're looking for a hands-on Team Lead to own how the Appointment Scheduling team runs — the process, planning, and delivery — and to drive its technical direction. You'll grow the engineers around you, keep the team healthy and shipping, and carry our platform into the AI age: an AI-augmented development lifecycle where agents do real work across design, code, test, and review, and a product where booking is conversational, availability is intelligent, and every answer is grounded in real, verified data.

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What You'll Do

Team & Delivery Leadership

  • Own the team's planning, prioritization, and delivery — the process and the day-to-day execution — ensuring the Appointment Scheduling team ships reliably at enterprise scale.
  • Grow and coach engineers at all levels (including senior and principal ICs); keep the team engaged, healthy, and improving.
  • Partner closely with the Principal Engineer to translate the hardest architectural decisions into reliable, shipped product.
  • Collaborate with Product and Design so that what ships solves the customer's actual problem, not just the technical one.

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Technical Direction

  • Own the overall technical direction for your area of the scheduling platform: the availability and booking engine, routing and reminders, and the online/branch/kiosk/queue/virtual channel experiences built on top.
  • Make the mature, business-critical scheduling core safer and faster to change — through pragmatic modernization, improved test coverage, and cleaner API surfaces — without big-bang rewrites.
  • Shape and evolve the platform's data architecture (SQL Server, PostgreSQL) and service boundaries (Spring Boot, Scala/Akka) to support scale and AI extensibility.
  • Maintain Engageware's reliability bar: the scheduling platform cannot let a customer down.

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AI-Augmented Development Lifecycle

  • Lead the team's adoption of an AI-augmented SDLC — putting AI agents (built on Claude) to work across design, code generation, test authoring, code review, and legacy modernization.
  • Set the team's norms and guardrails for AI-assisted development, with a strong test and CI/CD backbone ensuring AI-generated changes ship fast and safely.
  • Stay current on agentic development patterns (including MCP-based tooling) and raise the team's fluency over time.

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AI in the Product

  • Bring intelligent capabilities into the Appointment Scheduling product where they earn their place: conversational and assisted booking, smarter availability recommendations, reduced no-show rates, and proactive engagement.
  • Ensure all AI-driven features are grounded in real, verified availability data — never hallucinated — and are evaluated honestly against clear success metrics.
  • Partner with the Principal PM to align AI product bets with customer value and the broader scheduling roadmap.

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What We're Looking For

Must-have qualifications:

  • A track record of leading an engineering team to deliver: owning process, planning, and outcomes, while staying technically hands-on. You've shipped product, not just run a team.
  • Depth in the Appointment Scheduling tech stack: JVM backend (Java / Spring Boot, Java 17) and modern TypeScript front ends (React and/or Angular), with comfort in high-throughput services and the relational data behind them.
  • Experience modernizing large, mature, business-critical systems — making them safer and faster to change without disrupting the business.
  • Fluency with AI coding agents and AI-augmented development; ideally you've helped a team adopt AI across the SDLC, and you've shipped real LLM/AI features into production with clear-eyed judgment about where AI helps and where it doesn't.
  • Genuine product sense: you care about the booking experience the customer feels, not only the architecture behind it.
  • Based in the United States, with willingness to travel occasionally for team and customer meetings.

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Nice to Have

  • Prior experience with scheduling, calendaring, availability modeling, or resource-optimization problems.
  • SQL and relational data depth; API design and integration experience at enterprise scale.
  • Background in financial services, banking, credit unions, healthcare, or retail technology.
  • Experience exposing platform capabilities to AI agents via MCP or similar patterns.

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Our Stack

Knowing our stack is not a requirement, but this is what you'll be working with:

  • Backend: Mature Java scheduling engine; Spring Boot (Java 17) services; Scala/Akka services
  • Frontend: Modern Angular and React applications
  • Data: SQL Server and PostgreSQL
  • Infrastructure: Kubernetes on AWS
  • AI: Claude models (Anthropic), with MCP-based agent tooling



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