Note: The job is a remote job and is open to candidates in USA. Lyric is an AI-first, platform-based healthcare technology company focused on simplifying the business of care. The Engineering Manager will lead a team in modernizing the payment integrity platform, ensuring delivery outcomes while integrating AI-assisted engineering practices.
Responsibilities
- 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
- 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
- Partner with senior engineers to make sound architectural calls on the modernization: service boundaries, API contracts, data migration strategies, event-driven patterns, and frontend decomposition
- Keep the team honest about tech debt. You'll maintain a living view of what's been modernized, what's next, and what's intentionally deferred – and make sure 'deferred' doesn't quietly become 'forgotten.'
- Stay close to the data layer challenges. You don't need to tune every query yourself, but you need to understand where the database hot spots are and make sure the team is addressing them systematically
- Hire, retain, and grow strong engineers. You'll make staffing decisions, run effective 1:1s, give direct feedback, and create real growth paths – not just title bumps
- Foster a team culture of ownership, psychological safety, and honest communication. Engineers should feel comfortable raising concerns, pushing back on decisions, and admitting when something isn't working
- Balance workload across the team and across workstreams. You'll manage capacity proactively – not reactively after someone burns out or a workstream stalls
- Make security, privacy, and compliance non-negotiable in how the team builds. Least privilege, safe data handling, audit trails – these are engineering defaults
- Put real quality guardrails in place and enforce them: CI that blocks bad changes, automated tests that catch regressions, structured logging, and observability that surfaces issues before customers do
- Own incident response for your team's domain. When something breaks, you drive root cause analysis and make sure fixes are durable, not duct tape
- Work with product, analysts, and business stakeholders to translate business priorities into engineering plans with honest trade-offs and pragmatic milestones
- Represent engineering in cross-functional planning. You'll push back when timelines are unrealistic and commit when they're achievable – and the team will trust your judgment on the difference
- Communicate up and out clearly: delivery status, risks, staffing needs, and technical direction – without requiring anyone to ask twice
Skills
- 8+ years in software engineering, with at least 3 years in engineering management – leading teams, not just projects. You've managed hiring, performance, and delivery for teams of 5+ engineers
- 5 + years in C# and modern .NET (Core and beyond). You've personally done meaningful refactoring and migration work in large codebases. You're not managing from a spec – you can read the code, spot problems in a PR, and have credible architectural opinions
- 8 + years SQL Experience – schema design, query tuning, performance troubleshooting. You've managed teams working on data-heavy applications and you understand the database challenges firsthand
- You actively use AI coding tools – Cursor, Claude Code, Codex, or similar – and you've coached others on using them effectively. You have a point of view on how AI tools change engineering workflows, review practices, and team productivity
- Experience with distributed systems – Kafka, event-driven architectures, or hybrid database environments (SQL Server + Postgres)
- Familiarity with Angular and/or React/Next.js – enough to guide frontend architecture decisions and review frontend work meaningfully
- You've built AI-assisted engineering practices at the team level: repo instructions for agents, CI guardrails for AI-generated code, task decomposition patterns, and ways to measure the productivity impact
- Experience with progressive delivery – feature flags, canary deployments, blue-green – and you've used these to de-risk large migrations
- You communicate clearly and lead with low ego. Straightforward status updates, honest trade-off conversations, direct feedback delivered with respect. You build trust by being consistent and transparent
- Background in regulated domains (healthcare, fintech, payments) where compliance isn't optional and 'move fast and break things' will get you fired
Company Overview
Company H1B Sponsorship