# Rula — Engineering Manager - AI/ML (Remote)

- Generated: 2026-09-22 05:17:29 PM EDT
- Original/canonical posting: https://wellfound.com/jobs/4748857-engineering-manager-ai-ml-remote
- Provider: Wellfound
- Posted: 2026-09-21 07:27:49 PM EDT
- Elapsed since posting: represented by the provider's relative posting label and approximate Eastern timestamp when available
- Applicants: Not disclosed
- Work model/location: Remote — United States, excluding Hawaii
- Compensation: $208,000-$260,000 annually
- Travel: Quarterly team gatherings mentioned; percentage not disclosed
- Positioning track: Technical manager
- Fit outcome: PASS — 92%

## Direct-match strengths

Player-coach AI engineering leadership, distributed cloud systems, MLOps and AI observability, production LLM/RAG features, search and retrieval, evaluation, LLM-as-judge, human review, clinical safety, hiring, and regulated healthcare technology.

## Hard or material gaps

Keith's direct feature-store ownership and recent search-ranking product depth are less extensive than his broader data-platform, retrieval, evaluation, and production-AI record. Mental-healthcare workflows are new, though healthcare and regulated-software experience is direct.

## Evidence map

1. AI/ML engineering management (weight 3, evidence 3/3) — Built and led an 11-person production AI team.
2. Distributed backend and cloud systems (weight 3, evidence 3/3) — Direct AWS, APIs, microservices, containers, and data-platform work.
3. Core ML infrastructure (weight 3, evidence 2/3) — Direct MLOps, model deployment, evaluation, and observability; feature-store depth is lighter.
4. Production LLM/RAG/search features (weight 3, evidence 3/3) — Direct production LLM, RAG, vector retrieval, and workflow systems.
5. Product and platform delivery concurrently (weight 3, evidence 3/3) — Owned both user applications and reusable platform foundations.
6. Regulated healthcare and HIPAA (weight 2, evidence 3/3) — Direct FDA/HIPAA-facing healthcare technology.
7. AI evaluation and safety (weight 2, evidence 3/3) — Direct LLM-as-judge, human review, guardrails, bias, and monitoring.
8. Remote and compensation (weight 2, evidence 3/3) — Fully remote and maximum pay exceeds $200K.

## Keyword diagnostic

Strong dual-mandate fit across user-facing AI, foundational ML platforms, evaluation, clinical safety, and senior-team leadership.

## Full normalized job description

We believe that mental health is just as important as physical health. We recognize that mental health issues can be complex and multifaceted, and we are dedicated to treating the whole person, not just the symptoms.
We aim to create a world where mental health is no longer stigmatized or marginalized, but rather is embraced as an integral part of one's overall well-being.
We believe that by providing quality care that is both evidence-based and compassionate, we can empower individuals to take charge of their mental health and achieve their full potential. We are passionate about making a positive impact on the lives of those struggling with mental health issues and we strive to be a force for positive change in the field of mental healthcare.
Rula is a remote-first company. We currently hire in most U.S. states, with the exception of Hawaii.
About the Role
We are seeking an Engineering Manager for AI/ML to enable Rula’s AI Engineering team through technical leadership across both applied product capabilities and foundational ML platforms. This person will be responsible for guiding a highly AI-native group of Senior and Staff engineers to rapidly deliver user-facing features such as transcript summarization and search relevance, while simultaneously architecting our core AI/ML infrastructure such as feature store and AI observability platform. This person will apply a balance of strong execution speed, Radical Candor in their coaching, and rigorous clinical safety sense to ensure our solutions and models scale safely. You will be at the vanguard of Rula's AI engineering, shaping a culture of high talent density and driving technological synergy that directly transforms how mental healthcare is delivered and experienced.
Required Qualifications
8+ years of professional software engineering and machine learning experience, including 5+ years designing, scaling, and deploying distributed backend systems in cloud environments (AWS, GCP, etc.)
3+ years of direct engineering management experience, with a proven track record of hiring, retaining, and directly managing high-performing Senior and Staff-level engineers.
3+ years of experience technically leading or building core ML infrastructure, such as feature stores, MLOps pipelines, model deployment systems, or AI observability platforms.
2+ years of experience directing or developing production-grade applied AI features, specifically focusing on LLM integrations (e.g., NLP, transcript summarization, RAG) or search, ranking, and relevance engines
Proven operational track record of concurrently managing the delivery of both user-facing product features and backend infrastructure platform work across multiple production release cycles.
Preferred Qualifications
Regulated Industry Experience: Experience shipping advanced AI systems in high-stakes, regulated environments (such as HealthTech or FinTech), with a proven ability to balance rigorous privacy, compliance (e.g., HIPAA), and safety standards without grinding engineering velocity to a halt.
Advanced AI Evaluation Expertise: Deep, hands-on experience designing rigorous, production-ready evaluation frameworks for LLMs—combining automated metrics, LLM-as-a-judge, and Human-in-the-Loop (HITL) processes specifically aimed at mitigating hallucinations and bias in mission-critical applications.
AI-Augmented Engineering Philosophy: A strongly defined, practiced philosophy on using AI to multiply engineering output. We are looking for someone who doesn't just build AI, but actively deploys cutting-edge AI dev tools (e.g., coding agents, advanced IDE integrations, automated testing bots) to push an already high-performing team to hyper-efficiency.
Framework for Dual-Mandate Prioritization: Nuanced experience and a clear, communicable framework for managing the specific tension between short-term product delivery and long-term platform investments, demonstrating exactly how they prioritize technical debt and infrastructure scaling against aggressive feature sprints.
We're serious about your well-being! As part of our team, full-time employees receive:
100% remote work environment:
Working hours to support a healthy work-life balance, ensuring you can meet both professional and personal commitments (must be based in United States, currently not hiring in Hawaii)
Attractive pay and benefits
: Full transparency of pay ranges regardless of where you live in the United States
Comprehensive health benefits
: Medical, dental, vision, life, disability, and FSA/HSA
401(k) plan access
: Start saving for your future
Generous time-off policies
: Including 2 company-wide shutdown weeks each year for self-care (for most employees)
Paid parental leave
: Available for all parents, including birthing, non-birthing, adopting, and fostering
Employee Assistance Program (EAP)
: Supporting your mental and physical health
Quarterly department stipend
: Fun team-building activities or in-person gatherings
Community and employee resource groups
: Participate in groups that celebrate employee identity and lived experiences, fostering a sense of community and belonging for all
Home office stipend:
New hire home office stipend & $50 monthly stipend to help cover internet or cell phone expenses
Wellness at Rula program:
Year-round wellness initiatives and a $50/month wellness stipend
Our team
We believe that diversity, equity, and inclusion are fundamental to our mission of making mental healthcare work for everyone.  We are dedicated to having a culture of inclusion that will support our employees in feeling safe, seen, heard, and valued.

## Artifact metadata

- Resume: https://bit.ly/4jg5UMD
- Cover letter: https://bit.ly/4ySRAOQ
- Validation: PASS — 2-page resume (924 words), 1-page cover letter (191 words); PDF geometry, bounds, annotations, links, and visual pages verified.
- Google Drive used: No