Senior Engineering Manager, Software

Verto Health•Toronto, ON

9d•CA$150,000 - CA$200,000•Remote

About The Position

Verto Health is a health technology company focused on solving data fragmentation and interoperability challenges in healthcare. Their AI-enabled platform unifies clinical data from various sources to provide actionable insights for health systems and value-based care organizations. The Senior Engineering Manager, Software role is crucial for ensuring the reliable and scalable deployment of Verto's software. This position involves leading the engineering team, setting technical standards, and overseeing production releases. A significant aspect of the role includes managing NLP pipelines that convert unstructured clinical data into structured formats, a key differentiator for Verto's clients. The manager will also focus on enhancing the team's and colleagues' utilization of AI technologies. The role requires translating vague business goals into buildable projects, reporting to the CIO, and collaborating closely with Product and Data & AI leadership.

Requirements

6+ years of engineering experience with at least 2 years of leadership experience recently leading and growing agile engineering teams, respected as both an engineer and a manager.
Hands-on across a modern stack (Python, Ruby, JavaScript/TypeScript) and frameworks (Rails, Flask, Angular, Vue.js).
Solid command of Linux, Kubernetes, Docker, and CI/CD, with experience tuning real infrastructure on a major cloud (Azure, AWS, or Cloudflare).
Experience putting Generative AI into products and running NLP, machine learning, or analytics pipelines, plus daily use of AI development tools.
Comfortable across multi-database setups (PostgreSQL, Clickhouse, Elasticsearch, Redis).
A bachelor’s degree or higher in Computer Science, Engineering, or a related field.
A strong communicator who can align a room on a complex system and explain it just as well to people who are not engineers.
A genuine collaborator who works shoulder to shoulder with the team and across functions, and is at ease finding the simplest workable route through a messy problem.

Nice To Haves

Prior working experience in a product-led tech company is highly valued

Responsibilities

Build, grow, and lead the engineering team, set the technical bar, and own what ships to production.
Develop the next set of technical leads, and run hiring, onboarding, and the co-op program end to end.
Keep delivery predictable by managing to outcomes and sprint completion rather than story points, and protect the team from churn and micromanagement.
Own the roadmap for our NLP pipelines, working a steady loop of better quality, then lower cost, then faster inference.
Bring infrastructure cost and inference time down by evaluating serverless and edge options, and own cloud and tooling vendor decisions.
Get the team using frontier AI coding tools every day, and set up ways for non-technical colleagues to contribute through AI.
Run the Architecture Review Board and make the big system-design calls, setting clear boundaries and strong observability.
Protect a standing buffer for tech debt and research, and keep the codebase and internal tooling healthy.
Own estimates and scoping for new work, keeping scope simple and being clear up front about whether something is product or custom.
Partner with Product and Data & AI to turn clinical and business needs into solid backend work.
Own data ingestion and integration work for enterprise clients, and step into client technical conversations and data work when needed.
Manage shared delivery timelines, raise risks early with a plan to resolve them, and keep compliance reporting (such as SR&ED and IRAP) on track.
Own the budget for AI tooling, cloud, and R&D, and match people to the priorities that matter most.
Track who is working on what across projects, flag budget issues early, and help build the annual plan for your area.