PerfectServe’s mission is to accelerate speed to care by optimizing provider schedules and routing communications — including messages, pages, calls, and alerts — to the right place at the right time in any care setting. By facilitating real-time information sharing, building better schedules, and automating important clinical workflows, we believe we can help our customers advance patient care and improve the well-being of their clinicians.
Leading analyst firms like Gartner® and KLAS Research have consistently validated our approach:
- In 2026, PerfectServe was named highest in execution and furthest in vision in the Gartner Magic Quadrant™ for Clinical Communication and Collaboration — the clear segment leader.
- PerfectServe also received two Best in KLAS awards in 2026 — one for physician scheduling and another for ambulatory clinical communications. That makes for 11 Best in KLAS awards over the past 9 years.
If you're looking for a well-established, tech-forward company full of smart people doing meaningful work, you've found the right place!
PerfectServe is a leading healthcare communications platform that connects providers, patients, and care teams to improve clinical collaboration and patient outcomes. We are seeking a Full Stack AI Engineer to join our R&D organization and play a central role in bringing AI capabilities to production across the platform. This is a core, high-impact role responsible for defining AI architecture standards, shipping production AI features, establishing governance and evaluation frameworks, and partnering directly with R&D leadership to shape the AI roadmap.
Essential Functions
- Design AI integration patterns and architecture standards across the SaaS platform
- Integrate LLM APIs (OpenAI, Anthropic, AWS Bedrock) into production features
- Build RAG systems, vector search, and embedding pipelines
- Optimize latency, inference cost, and hallucination guardrails
- Establish model evaluation, benchmarking, and observability processes
- Define cost controls, usage monitoring, and security/PHI handling constraints
- Evaluate use cases with Product for ROI and feasibility
- Advise leadership on build vs. buy decisions for AI capabilities
Qualifications:
- 5+ years software engineering experience with strong Python backend skills
- Production experience with LLM APIs, RAG systems, embeddings, and vector databases
- Cloud-native architecture experience, preferably AWS
- Experience in regulated or security-conscious environments
- Product-minded systems thinker, comfortable with ambiguity and executive communication
This is not a research role. This is a builder role.
Why Join PerfectServe?
At PerfectServe, we are transforming healthcare communication and collaboration to help clinicians deliver better care. You’ll work with a dedicated and mission-driven team in an environment that values growth, transparency, and innovation.
We offer a salary range of $130,000-170,000 USD per year, with compensation tailored to your background, strengths, and potential to grow within the team. The salary range listed for this role reflects our commitment to pay transparency and is based on market data, internal equity, and the scope of responsibilities. compensation will be determined by a combination of factors, including the candidate’s experience, skills, and the specific team or product area they support. We regularly review compensation across the company to ensure fairness and consistency. If you are a current employee and have questions about how your compensation aligns with our ranges, we encourage you to speak with your manager or People Operations.
- Remote first work environment
- Health, Dental, Vision, Life and Disability Insurance options available day one.
- 401K - with match and immediately vested.
- 17 company holidays, 2 floating holidays plus competitive paid time off policy
- Internal Advancement Opportunities
PerfectServe offers unified healthcare communication solutions to help physicians, nurses, and care team members provide exceptional patient care. PerfectServe’s cloud-based solutions enhance patient safety and reduce provider burnout by automating workflows, speeding time to treatment, optimizing shift schedules, empowering nurse mobility, and engaging patients in their own care.
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