Senior Software Engineer (AI)

Location: Remote, USA

Salary: $110,000–$145,000 annual

Company

hirify.global develops regulated healthcare products that support care teams and members with AI-enabled features.

What you will do

• Build full-stack features integrating LLM APIs and SDKs into member- and care-team-facing product surfaces.
• Own features end to end, including system design, model and SDK integration, evaluations, observability, and user experience.
• Prototype AI features with real users, learn from failures, and harden valuable prototypes for production.
• Design for safe and compliant AI use in healthcare, including decisions about autonomous versus advisory behavior and human-in-the-loop workflows.
• Work with product management, design, clinical operations, and data teams to identify high-value AI opportunities and provide trustworthy context.
• Contribute to the team’s prototyping process, evaluation discipline, and quality standards.

Requirements

• 4+ years of engineering experience.
• Strong full-stack product engineering skills and a track record of shipping working software.
• Experience integrating LLM APIs or SDKs into a shipped product, or closely related production experience.
• Strong product sense and focus on product adoption and measurable value.
• Ability to turn well-scoped, high-value ideas into working products with decreasing guidance over time.
• Experience building evaluations or quality measurement for AI features, or a clear understanding of the need for them.
• Fluent daily use of AI assistants for engineering, with judgment about when to trust their output.
• Interest in mission-oriented work and ability to partner with clinical and design experts.

Nice to have

• CS degree or equivalent.
• Experience in regulated or compliance-heavy environments, including HIPAA or SOC 2.
• Experience building AI-native product features from scratch, including their evaluations.
• Design sensibility sufficient to prototype UX independently.
• Exposure to clinical operations or collaboration with clinical staff as end users.
• Hands-on RAG experience, including embeddings, vector search, and grounding LLM output in trusted context.
• Familiarity with agentic patterns such as tool or function calling, structured outputs, and multi-step orchestration.
• Experience with LLM evaluation and observability tools such as Braintrust or LangSmith, and LLM-as-judge techniques.
• Comfort with a modern TypeScript, Node, and React stack, including streaming and latency-sensitive LLM UX.

Culture & Benefits

• Remote work in the USA.
• Health insurance, life insurance, and retirement benefits.
• Participation in the company’s equity program.
• Paid vacation and sick leave.
• Equal opportunity employment and a focus on diversity.