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# Forward Deployment Engineer, AI – US 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 2026Published32Listing views3Application actions5 Oct 2026Apply before  Opportunity details

## About this role.

AI SummaryPerfectServe is hiring a Forward Deployment Engineer to deploy and improve production AI voice-agent solutions for healthcare customers. The role combines Python backend engineering, LLM evaluation, prompt tuning, observability, performance optimization, and customer-facing implementation ownership. The engineer will lead customer go-lives, troubleshoot production issues, and automate onboarding while maintaining PHI, security, and cost-control requirements. Success requires experience operating GenAI systems in production, cloud-native architecture—preferably AWS—and the ability to translate customer needs into reliable technical configurations.

## 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

5/5GuidedFull ownership

### Communication Load

5/5IndependentCollaborative

AI insightThis is a technically demanding production AI role because it requires ownership across deployment, backend development, evaluation, latency and cost optimization, and healthcare security constraints. The customer-facing go-live responsibility and ambiguity of forward deployment work add significant operational complexity.

## Salary analysis

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

Estimated job medianMarket rate$130,000US market range$115k–$155k0$171k

AI insightThe disclosed US yearly salary range is $120,000-$140,000 USD, with a midpoint of $130,000. This is broadly competitive for a mid-level forward deployment/software engineer with production LLM experience; an estimated US market range is $115,000-$155,000 annually, varying by AI depth, healthcare-domain experience, and location.

## 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)[Backend Engineering](https://jobicy.com/jobs?search_keywords=Backend%20Engineering.md)[Conversational AI](https://jobicy.com/jobs?search_keywords=Conversational%20AI.md)[LLM Evaluation](https://jobicy.com/jobs?search_keywords=LLM%20Evaluation.md)[Prompt Engineering](https://jobicy.com/jobs?search_keywords=Prompt%20Engineering.md)[Observability](https://jobicy.com/jobs?search_keywords=Observability.md)[Healthcare Data Security](https://jobicy.com/jobs?search_keywords=Healthcare%20Data%20Security.md)

Sample interview questionsHow would you design an evaluation suite for a healthcare AI voice agent before and after a customer deployment?I would start by defining customer-specific workflows, safety requirements, and measurable acceptance criteria. I would build a versioned test set containing representative, edge-case, and adversarial conversations; score task completion, factuality, escalation behavior, latency, and PHI-safety outcomes; and run it automatically on prompt, model, and configuration changes. After launch, I would use sampled production traces and user feedback to identify regressions and expand the test corpus.

Describe how you would reduce hallucinations in an LLM-based clinical communications workflow.

I would constrain the system to approved sources and clearly define tasks the model may and may not perform. Techniques would include retrieval with citations or structured tool calls, schema validation, deterministic routing for high-risk actions, confidence thresholds, and human escalation paths. I would also monitor unsupported-answer rates and investigate failures using trace-level observability.

A new customer needs a customized deployment quickly, but repeated manual configuration is slowing implementation. What would you do?

I would identify the repeated configuration decisions and convert them into reusable templates, validated configuration schemas, and automated provisioning workflows. Customer-specific differences should be represented as declarative settings rather than code forks wherever possible. I would add preflight checks and deployment runbooks so the implementation is repeatable, auditable, and easier for other engineers to support.

How would you balance inference quality, latency, and cost for a production voice AI agent?

I would establish service-level targets for response time, quality, and per-interaction cost, then instrument each stage of the request path. I would use model routing, smaller models for simpler tasks, prompt and context reduction, caching where appropriate, streaming responses, and targeted retries. Any optimization would be validated against the evaluation suite to ensure cost or latency gains do not reduce safety or task success.

How do you communicate a production AI issue to both an executive customer stakeholder and an internal engineering team?

For the customer stakeholder, I would provide a concise impact statement, affected workflow, current mitigation, ownership, and next update time without exposing unnecessary technical detail. For engineering, I would supply timelines, traces, reproduction steps, scope, suspected causes, and clear next actions. In both cases, I would communicate uncertainty honestly and document the final root cause and preventive measures after resolution.

### 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 $120,000 to $140,000 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.

### 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/152605-forward-deployment-engineer-ai-us-remote.md)

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