Our mission is simple but ambitious: to use AI to fix the broken economics and lost humanity of care. If you want to move fast and help build the future of healthcare with heart, you belong at Arya.

About the Role

We’re looking for a Senior Software Engineer in AI to join our team and embed intelligence into Arya’s workforce platform. You won’t be building foundation models—but you’ll be working with LLMs and AI toolkits to orchestrate workflows, automate decision-making, and improve how customers interact with Arya. Our team partners with Google’s Vertex AI group to shape their Agent development kit, and we’re looking for an engineer who can turn these cutting-edge tools into production-ready solutions for scheduling, shift eligibility, workforce management, and more.

As a senior member of the engineering team, you’ll work closely with our Principal Architect and own AI-driven projects end-to-end: designing, prototyping, and deploying systems that make work smarter, more automated, and more intuitive for our customers.

What You'll Do

Design and implement AI-powered workflows using Vertex AI Agents, Pydantic, Bland.ai and other orchestration frameworks.

Integrate LLMs into customer workflows (e.g., natural language scheduling, eligibility insights, onboarding automation).

Build scalable APIs and services that serve AI features reliably in production.

Implement evaluation, monitoring, and safety checks to ensure AI systems are accurate, fair, and trustworthy.

Collaborate with Product and Engineering to identify practical, high-impact AI use cases.

Document integration patterns and best practices for AI deployment.

Provide technical leadership and mentorship on AI integrations.

What This Role Is Not

❌ You won’t be training LLMs or building foundation models from scratch.

❌ You won’t be focused on academic research or publishing papers.

❌ You won’t be working in isolation — this role is highly collaborative with product and engineering teams.

❌ You won’t be building experimental prototypes only; you’ll be delivering production-ready, customer-facing AI features.

This role is about applied AI engineering: using the best tools available (Vertex AI, OpenAI APIs, RAG pipelines, vector databases) to solve real-world customer problems.

What We’re Looking For

5+ years of software engineering experience, with 2+ years working with LLMs or AI frameworks.

Strong programming skills in Python or Node.js; familiarity with Pydantic and MCP architecture.

Expert in SQL and proficient with Postgres optimization.

Hands-on experience with Vertex AI, OpenAI, or other model APIs.

Familiarity with CI/CD pipelines and cloud environments (GCP preferred).

Experience designing APIs and backend services that integrate AI features at scale.

Clear communication skills and a collaborative, pragmatic mindset.

Nice to Have

Experience with retrieval-augmented generation (RAG) pipelines and vector databases.

Exposure to compliance-aware AI systems in regulated industries.

Contributions to open-source AI/LLM frameworks.

Knowledge of monitoring/evaluation techniques for AI systems.

What to Expect in the First 90 Days

By Day 15 — Onboarding & Environment Setup

Fully onboarded into Arya’s AI stack and workflows.

Review existing AI integrations (Vertex AI, orchestration pipelines).

Ship one small improvement to an AI workflow or feature.

Draft notes on gaps or opportunities for automation.

By Day 30 — Initial Contributions & Familiarity

Ship your first AI-driven feature (e.g., LLM-powered scheduling helper, onboarding workflow) to staging or production.

Implement monitoring or evaluation improvements for an existing AI pipeline.

Partner with Product to scope a new AI use case.

Contribute to code reviews for AI-related PRs.

By Day 60 — Ownership of Integration Scope

Fully own one or more AI workflows from experimentation through monitoring.

Ship at least one high-impact improvement (e.g., reducing latency, improving response reliability).

Document and share best practices for LLM integrations.

Join customer calls to understand workflow pain points where AI can help.