Lead Software Engineer - MLOps at Sunlife

Provide technical leadership for the MLOps squad within the Analytics Platform, influencing architecture and standards across multiple teams
Design, build, and evolve production‑grade MLOps and ML platform capabilities , including model lifecycle management, CI/CD, evaluation, monitoring, and governance
Spend ~ 60% hands‑on in software engineering , building high‑quality, testable, maintainable services, frameworks, APIs, and shared libraries that enable ML and GenAI at scale
Spend ~ 40% on platform, cloud, and MLOps enablement , ensuring solutions are secure, scalable, observable, and cost‑effective
Act as a technical authority for AWS‑based ML platforms , leading design decisions and guiding adoption of new cloud and GenAI services
Establish and evolve engineering and MLOps standards , patterns, and best practices across squads
Partner closely with Architecture, Security, Risk, and Product teams to reduce delivery, operational, and model governance risk
Lead by example through code reviews, design reviews, incident analysis, and operational improvements
Mentor senior and intermediate engineers, raising the overall technical bar without direct people management
What you need to succeed
A deep software engineering background , with a strong track record of building and operating large‑scale, production systems
Extensive hands‑on experience with AWS in production , including infrastructure design, deployment, and optimization
Strong experience with
Distributed systems and cloud‑native architectures CI/CD pipelines and automation
Observability, reliability, and incident response
Practical experience with MLOps, ModelOps, ML platforms, or LLMOps in enterprise environments
Proficiency in one or more of: Python, Java, Scala , and Infrastructure‑as‑Code tooling (Terraform / CloudFormation)
Ability to operate at Lead scope , influencing architecture and decisions across multiple teams and domains
Exceptional communication skills, with the ability to explain complex technical concepts to both technical and non‑technical stakeholders
Preferred skills:
Deep familiarity with AWS analytics, ML, and GenAI services , including evaluation and monitoring tooling
Experience designing or supporting enterprise MLOps / ML platform frameworks used by multiple teams
Strong understanding of security‑first design , governance, and compliance in regulated environments
Experience balancing innovation with operational supportability in platform teams
Proven ability to mentor and influence without formal authority
Strong product and business awareness, enabling pragmatic technical trade‑offs
We value analytical thinking and continuous learning. Through training and coaching, you can improve your data literacy and apply insights in meaningful ways, regardless of experience level.

Lead Software Engineer - MLOps

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