Senior Data Developer

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Senior Data Developer

R5650

Location

Toronto

Career Track

Technology

Senior Data Developer

Apply Now

This role is eligible for our hybrid work model: 2 days in-office

This job posting is for an existing, currently vacant position.

Senior Data Developer
 

ABOUT THE TEAM

The Global Platform Engineering (GPE) team, within the Data & AI/ML group, builds the foundational platforms that power Priceline’s most strategic data, ML, and AI initiatives. GPE builds the CLIs, SDKs, APIs, services, frameworks, and operational systems that let data scientists, ML engineers, and product teams go from an idea to a governed, production-grade model or AI application on a single paved path. Our charter spans the full ML/AI lifecycle: from project scaffolding and feature engineering to training, serving, evaluation, monitoring, and agent orchestration.

IN THIS ROLE YOU WILL GET TO

Platform Engineering

  • Build and operate the AI platform layer: AI and MCP gateway services for model routing, cost and rate limiting, prompt and version management, evaluations, guardrails, safety, and observability across both internal applications and external consumers.

  • Design, build, and evolve the developer-facing interfaces of our ML and AI platforms: CLIs, SDKs, APIs, project templates, scaffolding engines, and self-service UIs that turn complex infrastructure into a single, governed paved path from idea to production.

  • Build reusable AI/ML patterns and reference implementations such as agent frameworks, evaluation harnesses, tracing, ML Metadata tracking packaged as platform capabilities other teams can adopt without rebuilding.

DevOps, SRE & Production Operations

  • Own CI/CD pipelines and GitOps-based deployment workflows for platform services and the ML/AI workloads that run on them.

  • Use infrastructure-as-code to provision and manage cloud and Kubernetes resources; automate scaling, capacity, and routine operations.

  • Define and enforce SLOs for platform services and customer ML/AI workloads; implement logging, metrics, alerting, on-call response, and post-incident review.

  • Embed security, IAM/RBAC, and policy controls into platform primitives so that “the secure way” is also “the easy way” for platform users.

Technical Leadership

  • Write design docs, drive architecture reviews, and make trade-offs that the team and partner teams can rally around.

  • Raise the engineering bar through code review, mentorship, and pairing; coach engineers across the broader Data & AI/ML org on platform best practices.

  • Partner with product, enterprise architects, infrastructure, and security teams to align roadmaps and unblock adoption.

WHO YOU ARE

  • Bachelor’s degree in Computer Science or a related field, or equivalent practical experience.

  • 7+ years of progressively complex software engineering experience, with a meaningful portion of it building platforms, frameworks, or infrastructure products consumed by other engineers.

  • Strong production engineer in Python (proficiency in another systems language — Go, Java, or similar — is a plus); you write code that is well-tested, observable, and operable.

  • Hands-on experience building cloud-native systems on a major cloud provider (GCP strongly preferred; AWS/Azure considered), including managed data, ML, and serving services.

  • Deep experience with Kubernetes, container-based deployment, service mesh patterns, and GitOps-style CI/CD.

  • Solid Infrastructure-as-Code experience (e.g., Terraform) and a track record of automating away toil.

  • Practical experience operating AI/ML or GenAI workloads in production — pipelines, serving, evaluation, monitoring, retraining loops; familiarity with LLMOps concepts such as RAG, vector stores, prompt/version management, evaluations, guardrails, and agent frameworks.

  • Experience with data systems at scale: workflow orchestration, batch and streaming processing, warehouses/lakes, and the operational realities of large data pipelines.

  • Strong production-operations mindset: SLOs, observability, incident response, root-cause analysis, capacity and cost management.

  • Excellent collaboration and written communication; comfortable driving cross-team alignment through design docs and architecture reviews.

  • An owner’s mindset and a bias for shipping; you make pragmatic trade-offs and bring others along.

  • Illustrated history of living the values necessary to Priceline: Customer, Innovation, Team, Accountability and Trust.

  • The Right Results, the Right Way is not just a motto at Priceline; it’s a way of life. Unquestionable integrity and ethics is essential.

NICE TO HAVE

  • Experience building developer platforms, internal developer portals, or self-service infrastructure products at scale.

  • Experience with AI gateways, model routing, evaluation/guardrail frameworks, or MCP-style tool/agent infrastructure.

  • Contributions to open-source platform, ML, or AI tooling.

  • Experience with feature stores, ML metadata systems, or experiment-tracking platforms.

  • Exposure to SRE best practices and error budgets specifically applied to AI/ML systems.

  • Background in high-traffic consumer or travel/e-commerce technology environments.

There are a variety of factors that go into determining a salary range, including but not limited to external market benchmark data, geographic location, and years of experience sought/required. In addition to a competitive base salary, certain roles may be eligible for an annual bonus and/or equity grant.

The salary range for this position is $130,000- $165,000K CAD

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