Software Development Manager - Replay

Company Overview

Lyric is an AI-first, platform-based healthcare technology company, committed to simplifying the business of care by preventing inaccurate payments and reducing overall waste in the healthcare ecosystem, enabling more efficient use of resources to reduce the cost of care for payers, providers, and patients. Lyric, formerly Claims Xten, is a market leader with 35 years of pre‑pay editing expertise, dedicated teams, and top technology.

Lyric is proud to be recognized as 2025 Best in KLAS for Pre‑Payment Accuracy and Integrity and is HI‑TRUST and SOC2 certified, and a recipient of the 2025 CandE Award for Candidate Experience. Interested in shaping the future of healthcare with AI? Explore opportunities /careers and drive innovation with #You To The Power Of AI. We’re a company at the intersection of Fin Tech and Healthcare, committed to simplifying healthcare payment integrity and creating value for health insurers, healthcare providers, and consumers.

We’re not a startup, but we move like one when it matters. Right now, we’re in the middle of a large modernization of our payment integrity platform: ripping out legacy .NET, rebuilding around clean APIs, fixing data bottlenecks, and getting the product ready for scale.

We’re looking for an Engineering Manager to lead the engineering team behind this modernization. You’ll own the delivery outcomes for a team of full‑stack and backend engineers building modular Angular frontends and resilient .NET microservices – and you’ll be hands‑on enough to unblock architectural decisions, review critical PRs, and jump into code when the situation calls for it. You’ll partner closely with product, UX, Dev Ops, and QA to keep the team shipping customer‑delighting features at a pace that matches our ambition.

This is what makes this role different: you’re not managing a team that happens to use AI tools – you’re building a team where AI‑assisted engineering is the default way of working. You’ve used Cursor, Claude Code, Codex, or similar tools yourself, and you know how to coach engineers on using them effectively. You understand the difference between an engineer who uses AI to go faster and one who uses it to avoid thinking.

Your job is to make sure the team stays on the right side of that line – and gets dramatically more productive in the process.

This is the core of the role:
Own the delivery roadmap for platform modernization – sequencing migration work, API extraction, and frontend decoupling into realistic, high‑impact milestones. Remove blockers before the team feels them. Whether it’s a cross‑team dependency, an unclear requirement, or a technical rabbit hole, you see it early and act on it. Hold the team to high engineering standards without micromanaging: clean PRs, meaningful test coverage, current documentation, and architecture decisions that are recorded and revisited.

Get hands‑on when it matters – reviewing critical design decisions, pairing on thorny migration problems, or stepping into code to unblock a stuck workstream.

What success looks like:
Modernization progresses predictably sprint over sprint. Legacy surface area shrinks measurably. Stakeholders trust the plan because the team keeps hitting its marks. Engineering quality improves alongside velocity – production incidents trend down, not up.

Build and scale AI‑assisted engineering practices:
Set the standard for how the team uses AI coding tools. That means establishing repo‑level agent instructions, prompt playbooks, review standards for AI‑generated code, and clear expectations for when AI output needs human scrutiny (always). Coach engineers individually on effective AI workflows – not just tool mechanics, but judgment: knowing when the agent is hallucinating, when to override, and when to step back and think before prompting.

Measure the impact. Track migration throughput, PR cycle times, test coverage growth, and defect rates to prove that AI‑assisted practices are actually working – and course‑correct when they aren’t. What success looks like:
The team ships meaningfully more, without a spike in bugs or rework. AI practices are embedded in team…