Sr Software Engineer Jobs in Alaska (NOW HIRING)

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 ClaimsXten, 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 at lyric.ai/careers and drive innovation with #YouToThePowerOfAI.

Applicants must already be legally authorized to work in the U.S. Visa sponsorship/sponsorship assumption and other immigration support are not available for this position.

We’re a company at the intersection of FinTech 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 starting on 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 on Full Stack Engineer to build intuitive, performant web experiences backed by scalable, event driven services. You’ll own end to end delivery‑from modular Angular frontends (including micro frontend strategies) to resilient .NET microservices‑working closely with product, UX, DevOps, and QA to ship customer delighting features at scale. If you thrive in fast paced environments, care deeply about clean architecture and DX, and enjoy solving complex UI/UX and distributed systems challenges, this role is for you.

Here’s what makes this role different: you’re not just a .NET engineer who “also knowsAI.” We want someone who has already figured out that tools like Cursor, Claude Code, and Codex aren’t toys ‑ they’re force multipliers. You’ll use AI agents every day to tear through migrations, refactors, and test coverage that would take a traditional team weeks. But you also know when the AI is wrong, when to step in, and how to keep quality high. Think of it as having a junior engineer with infinite energy and zero judgment ‑ your job is to supply the judgment.

This is your superpower. You’ll:

• Use AI agents (Cursor, Claude Code, Codex) to blow through framework upgrades, refactors, API extraction, test scaffolding, and documentation - while catching hallucinations and preventing regressions before they hit a PR.
• Build reusable playbooks the team can actually follow: prompt templates, repo‑level agent instructions, migration checklists, review heuristics, and clear "definition of done" standards for AI‑assisted changes.

What success looks like:

• You measurably move the needle - more modules migrated per sprint, faster PR turnarounds - without a spike in production bugs.
• The team gets better because of you: PRs are clearer, test coverage grows, documentation stays current, and the same mistakes stop repeating.

You’ll:

• Upgrade legacy services to current .NET (LTS where it makes sense), untangling architecture boundaries and fixing the performance issues that have been “known” for years.
• Push toward a proper API‑layer architecture ‑ RESTful, versioned ‑ built for correctness and maintainability, not just “it works.”
• Get your hands dirty with SQL Server: query performance, indexing, transactional correctness. If there are data pipeline needs (Kafka, etc.), you’ll help build those too.

What success looks like:

• Legacy surface area shrinks sprint over sprint. Critical paths live in modern code. Fewer “oh, that’s still in the old system” conversations.
• APIs get faster and more reliable. Database hot spots stop waking people up at night.

You’ll:

• Build with security and privacy as defaults, not afterthoughts. Least privilege, safe data handling, the works. This is healthcare ‑ getting it wrong isn’t an option.
• Put real quality guardrails in place: automated tests that actually catch things, CI that blocks bad changes, structured logging, observability that tells you what’s happening before users do.
• Review code thoughtfully, have honest architectural conversations, and raise the bar without being a jerk about it.

What success looks like:

• Fewer severity‑1 incidents. When something does go wrong, root cause takes hours, not days.
• Automated test coverage grows meaningfully on modernized code. The team stops relying on “just test it manually.”