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# Forward Deployment Engineer, AI – Canada Remote

Review the role, location requirements, compensation details, and application process before deciding whether this opportunity fits your next career move.

[Apply for this job](#job-application)[View company](https://jobicy.com/company/perfectserve.md)Share5 Sep 2026Published27Listing views2Application actions5 Oct 2026Apply before  Opportunity details

## About this role.

AI SummaryPerfectServe is hiring a Forward Deployment Engineer to deploy, configure, and improve AI voice-agent solutions for healthcare customers. The role combines Python backend engineering, production LLM operations, customer implementation, and ownership of go-live and post-launch troubleshooting. Key work includes building evaluation suites, improving prompt quality and guardrails, optimizing latency and inference costs, and maintaining observability and PHI-security controls. This is a customer-facing engineering role in a regulated healthcare environment that requires translating business requirements into reliable production deployments.

## Role DNA

A quick view of the complexity, pace, ownership and collaboration implied by the job description.

### Job Complexity

4/5EasyHard

### Pace & Pressure

4/5RelaxedFast-paced

### Autonomy Level

4/5GuidedFull ownership

### Communication Load

5/5IndependentCollaborative

AI insightThe role requires production-grade LLM engineering alongside direct ownership of customer deployments in a security- and PHI-conscious healthcare setting. Candidates must balance technical depth in Python, cloud systems, evaluations, and observability with strong customer and executive communication.

## Salary analysis

Estimated compensation compared with the broader CA market for similar roles.

Estimated job medianHighly competitiveC$180,000CA market rangeC$140k–C$190k0C$209k

AI insightThe disclosed offer is CAD 165,000-195,000 yearly, with a midpoint of CAD 180,000. For the US market, an estimated annual base-salary range for a mid-level Forward Deployment/AI Engineer with production LLM, cloud, and regulated-industry experience is USD 140,000-190,000; actual compensation varies by location, company stage, and customer-facing scope.

## Core skills

Skills and capabilities most closely associated with this opportunity.

[Python](https://jobicy.com/jobs?search_keywords=Python.md)[LLM APIs](https://jobicy.com/jobs?search_keywords=LLM%20APIs.md)[Generative AI](https://jobicy.com/jobs?search_keywords=Generative%20AI.md)[AWS](https://jobicy.com/jobs?search_keywords=AWS.md)[Cloud-native architecture](https://jobicy.com/jobs?search_keywords=Cloud-native%20architecture.md)[AI evaluation](https://jobicy.com/jobs?search_keywords=AI%20evaluation.md)[Prompt engineering](https://jobicy.com/jobs?search_keywords=Prompt%20engineering.md)[Observability](https://jobicy.com/jobs?search_keywords=Observability.md)[Healthcare technology](https://jobicy.com/jobs?search_keywords=Healthcare%20technology.md)[PHI security](https://jobicy.com/jobs?search_keywords=PHI%20security.md)

Sample interview questionsHow would you design an evaluation suite for a healthcare AI voice agent?I would begin with a representative, privacy-safe test set covering common workflows, edge cases, ambiguous requests, escalation scenarios, and prohibited PHI-handling behaviors. I would define measurable criteria such as task completion, factuality, safety, latency, cost, and appropriate handoff, then automate regression testing for every prompt, model, or configuration change. I would combine automated scoring with targeted human review for high-risk clinical and customer-impacting interactions.

Describe how you would reduce the effort required to onboard each new AI customer.

I would map the existing onboarding process to identify repeated engineering tasks, configuration dependencies, and common failure points. Then I would create reusable configuration templates, validation checks, deployment automation, and self-service intake mechanisms for customer-specific data. I would measure onboarding duration, engineering hours, deployment defects, and time to first successful interaction to verify improvements.

How do you balance LLM response quality, latency, and inference cost in production?

I would instrument each stage of the request path to establish baselines for latency, token use, error rates, and quality outcomes. Depending on the workflow, I would use prompt reduction, caching, smaller or routed models, constrained outputs, retrieval optimization, and asynchronous processing where appropriate. Any optimization would be validated against evaluation suites so lower cost or faster responses do not weaken safety or task accuracy.

How would you handle a production issue reported shortly after a customer go-live?

I would first assess user impact and patient-safety or PHI risk, apply mitigation such as feature flags, rollback, or escalation paths, and communicate status clearly to internal and customer stakeholders. I would use logs, traces, model inputs and outputs, and configuration history to isolate whether the cause is a prompt, integration, data, infrastructure, or user-flow issue. After resolution, I would document the root cause, add regression coverage, and improve monitoring or deployment controls to prevent recurrence.

How do you translate a non-technical customer request into a safe AI deployment?

I clarify the underlying workflow, users, desired outcomes, exceptions, data sources, and success metrics before proposing a solution. I convert those requirements into explicit configuration, integration, security, and acceptance-test requirements, documenting assumptions and constraints in plain language. I then validate the implementation with stakeholders through scenario-based testing before production release.

### What is PerfectServe?

PerfectServe is a leading provider of clinical communication and physician scheduling solutions in the health IT space. The company was founded in 1997 and has grown steadily since then, with a notable jump after several major acquisitions were announced in 2019. PerfectServe now has 400+ employees, 30,000+ customers — spanning medical practices, hospitals, and health systems — and $100 million+ in annual revenue.

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.

At PerfectServe, you’ll have a unique opportunity to join a collaborative team with decades of experience that finds new ways to delight our customers every day. This involves consistent efforts to stay on the cutting edge of product development, which includes everything from implementing AI in new and existing solutions to brainstorming with customers about novel workflows. But you don’t have to be in product to make in impact — everybody at PerfectServe contributes to important work that moves the business forward.

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 Forward Deployment Engineer, AI, to join our Professional Services organization. This is a core, high-impact role responsible for deploying our AI product to new customers, reducing the effort it takes to bring each customer live, and continuously optimizing and extending our AI offerings.

Essential Functions:

* Help configure and rollout customers of our existing AI voice agent
* Build and run evaluation suites to validate behavior, catch regressions, and tune prompts as new customers are deployed
* Develop new features and fixes to the core product
* Optimize latency, inference cost, and hallucination guardrails
* Run and improve model evaluation, benchmarking, and observability across the product
* Monitor cost controls, usage monitoring, and security/PHI handling constraints
* Partner with Product and Customer Success to turn customer requirements into working, validated deployments, and own customer go-live, post-launch monitoring, and production issue debugging
* Help streamline and automate the onboarding process to reduce the engineering effort
required to bring each new customer live

Qualifications:

* 3+ years software engineering experience with strong Python backend skills
* 1+ years of production experience with LLM APIs, deploying and supporting GenAI systems at scale
* Cloud-native architecture experience, preferably AWS
* Experience in regulated or security-conscious environments
* Product-minded systems thinker, comfortable with ambiguity and executive communication
* Experience with voice or conversational AI a plus
* Comfortable translating non-technical customer requirements into working configuration

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 $165,000 to $195,000 CAD 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.

### Benefits:

* 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](https://www.perfectserve.com/) 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.

Show more

[Apply now >](https://jobicy.com/jobs/152601-forward-deployment-engineer-ai-canada-remote.md)

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