Senior AI Engineer
Job Description
Founded in 2014, League is the leading healthcare consumer experience (CX) platform, powered by artificial intelligence (AI), reaching more than 63 million people around the world and delivering the highest level of personalization in the industry. Payers, providers, and consumer health partners build on League’s platform to deliver high-engagement healthcare solutions proven to improve health outcomes. League has raised over $285 million in venture capital funding to date, powering the digital experiences for some of healthcare’s most trusted brands, including Highmark Health, Manulife, Medibank, and Shoppers Drug Mart.
The Role
We are seeking a Senior AI Engineer to join our AI & Data Group on the AI Orchestration team. This role is responsible for designing, building, operating and scaling the orchestration layer that powers League’s AI-driven healthcare experiences.
Sitting at the intersection of AI systems design, ML productionization, and distributed software engineering, you will take the probabilistic capabilities of large language models and engineer them into reliable, measurable, and scalable product experiences.
This is a hands-on senior engineering role for a practitioner who moves beyond prototypes to own the hard problem of making AI work at scale. You will translate leading edge AI innovation into reliable, secure, and compliant systems. Your work will directly impact how AI is operationalized across League’s digital health ecosystem—ensuring systems are scalable, observable, performant, and safe in a regulated environment.
AI Orchestration & Systems Design
- Design and build production-grade AI systems, including RAG pipelines, multi-step agents, and LLM-powered features.
- Make principled architecture choices regarding RAG vs. fine-tuning and agentic loops vs. simpler call-and-response patterns.
- Architect for long-term maintainability, ensuring systems fail gracefully and handle non-deterministic outputs predictably.
Evaluation & Quality Assurance
- Build comprehensive evaluation and observability frameworks to measure model accuracy, grounding, and quality drift.
- Implement automated test suites and "LLM-as-judge" pipelines to catch defects before they reach production.
- Set quality standards for AI components and drive improvements based on human feedback loops.
Production Engineering & MLOps
- Create production-quality Python services to wrap AI logic into secure microservices.
- Leverage AI coding assistants (Claude Code, Codex, Cursor, etc) to write the majority of your code, while still retaining ownership and deep understanding of the product created
- Own the model lifecycle, including versioning prompts as first-class code artifacts and monitoring for performance degradation.
- Manage the economics of LLM usage, balancing model performance against latency and cost
Collaboration & Technical Leadership
- Partner with Product, Data Science, and Backend teams to translate ambiguous requirements into technical specifications.
- Mentor junior engineers on AI craft, including embedding selection, vector store design, and prompt engineering precision.
- Actively reduce knowledge concentration by contributing to shared AI tooling and documentation.
- Contribute to roadmap planning and longer-term AI architecture decisions.
Platform Excellence & Innovation
- Establish and uphold standards for performance, security, privacy, and data governance within AI systems.
About You:
- Deep Technical Expertise: Extensive hands-on experience in software engineering and a strong understanding of the entire machine learning lifecycle
- Platform-Level Thinking: Proven ability to design and build scalable, distributed systems, ideally for machine learning or data-intensive applications
- MLOps Mastery: Demonstrated experience with MLOps tools and practices, including CI/CD for machine learning, model versioning, and feature stores
- Cloud Proficiency: Expertise with public cloud platforms (e.g., AWS, GCP, Azure) and a solid understanding of containerization and orchestration technologies like Docker and Kubernetes
- Data Fluency: A strong grasp of data engineering concepts, including data pipelines, data warehousing, and distributed data processing frameworks
Tech Stack:
- Cloud Platforms: Extensive experience with GCP and/or AWS, including core compute, storage, and networking services.
- Programming Languages: Expert-level proficiency in Python, familiarity with Go for backend services is a bonus.
- Data & AI Frameworks: Experience with big data processing platforms like Apache Spark, Apache Beam, Hadoop, etc
- Familiarity with modern machine learning frameworks such as TensorFlow, PyTorch, and scikit-learn.
- MLOps & Orchestration: Deep understanding of MLOps principles and hands-on experience with tools like Kubeflow, MLflow, LangChain or LLamaIndex.
- Experience with workflow orchestration tools like Airflow or a similar platform.
- DevOps & Infrastructure:Expertise in containerization and orchestration using Docker and Kubernetes.
- Hands-on experience with Infrastructure as Code (IaC) tools like Terraform
- Data Systems: Experience with both relational and NoSQL databases, and familiarity with data warehousing and streaming technologies. Experience with vector databases (Pinecone, ChromaDB, Mongo) and retrieval strategies (chunking, hybrid search, re-ranking) a definite bonus
Security-related Responsibilities
- Ensure access management is performed in compliance with the employee's role and responsibilities
- Responsibility and accountability for executing League's policies and procedures within the department/ team
- Notification of HR, Legal, Compliance & Security of any incidents, breaches or policy violations
- Compliance with Information Security Policies
CANADA APPLICANTS ONLY: The Canada-specific compensation range below for this full-time position is exclusive of bonus, equity and benefits. This range reflects the minimum and maximum target for base salaries for the position across all Canadian locations. The salary range is intentional to account for the performance and career progressions a Leaguer will experience in the role throughout their time at League. Where in the band you may land is determined by job-related skills/experience. Your recruiter can share more about the specific salary range specific to your skills and experience during the hiring process.
We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. If you are an individual in need of assistance at any time during our recruitment process, please contact us at [email protected].
- You should receive a confirmation email after submitting your application.
- A recruiter (not a computer) reviews all applications at League.
- If we see alignment with League's needs, a recruiter will reach out to learn more about your goals. The recruiter will also share the team-specific interview process depending on the roles you are exploring.
- The final step is an offer, which we hope you will accept!
- Prior to joining us, we conduct reference and background checks. Additional checks could be required for US Candidates, depending on the role you are exploring.
- Learn about our platform, leadership team and partners
- Highmark Health, Google Cloud, League: new digital front door to seamless care
- Former Providence President and Workday EVP of Corporate Strategy join League Board of Directors
- League raises $95 million USD in Series C to build world’s leading healthcare CX platform
- Forbes x League: The Platformization Of Healthcare Is Here
- Fast Company x League: If we want better innovations in healthtech, we need more competition
Work Location:
We have a mix of office-centric roles based in our vibrant Toronto office, and remote-eligible roles based anywhere in Canada or US. Each job posting will indicate where the role will be based. Regardless of the role’s posted location, all Toronto-area Leaguers (living within 65 km of our downtown HQ) collaborate in-office Monday through Thursday. Depending on your distance to the office, you’ll enjoy 10 or 20 Flexible Remote Days each quarter for focus and deep-work time. We are committed to fostering a meaningful work environment and connections for all Leaguers regardless of location.
Recognize and Avoid Employment scams. Practice safe job searching.
Scammers are getting craftier and leveraging fake job postings to get personal information. Know the warning signs and protect yourself from scammers. Learn more here.We are committed to ensuring fairness and transparency throughout our hiring process. League may use Artificial Intelligence (AI) tools to assist in the screening of applicants for this position. Please check out our stance on using AI in recruitment here.
