Level

RulaPosted today

L4

Engineering Manager - AI/ML (Remote)

Engineering Manager - AI/ML (Remote) at Rula scores 86 out of 100 on AI centrality, which makes it a Level 4 role on this board.

Remote (Remote - United States)seniorFullTime$208k-$260k

AI in this role

ragllm-integrationml-opsai-evaluationnlp

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.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

RagLlm IntegrationMl OpsAI EvaluationNlp

Questions you could be asked

  1. How would you design a retrieval step so the model answers from real data instead of guessing?
  2. How have you integrated a large language model into a production application?
  3. How do you monitor a model once it's live, and how do you know it needs retraining?
  4. How do you decide that one model's output is better than another's for a given task?
  5. What NLP problem have you worked on, and how did you measure whether it actually worked?

Adapt your resume

  • List these exact terms on your resume: Rag, Llm Integration, Ml Ops, AI Evaluation, and Nlp. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.

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