Job Specifications
This role is eligible for our hybrid work model: Two days in-office.
About The Team
The Global Platform Engineering team within Priceline’s Data & AI/ML product group powers some of Priceline’s most strategic initiatives by providing secure, scalable, and governed access to data, machine learning, and GenAI. We build core platforms that enable self-service development and deliver reliable, enterprise-ready solutions. If you enjoy working at the intersection of platform engineering and AI/ML at scale, this team offers a high-impact environment.
Why this job’s a big deal
As Priceline scales personalization, AI-driven optimization, and intelligent automation, a modern platform for data and AI/ML is mission-critical. In this role, you’ll help build and operate foundational systems that enable self-service AI/ML engineering, data engineering, MLOps/LLMOps, and GenAI workloads, while expanding access to trusted data and models. Your work will accelerate innovation across product and business teams at Priceline.
In This Role, You Will Get To
Build AI-powered platform frameworks and tooling
Build and maintain Python OOPS (object-oriented programming) services/frameworks and internal AI/ML platform tooling deployed to GKE with GitOps-based workflows.
Improve developer productivity around GenAI by delivering standard templates, reusable components, golden paths and self-serve workflows for AI/ML and GenAI use cases (e.g., RAG and Agentic AI agent-based patterns etc.) using modern AI multi-agent frameworks (e.g., LangChain/LangGraph/CrewAI/Autogen etc.).
Contribute to enterprise governance and enablement for the GenAI ecosystem via guardrails and observability for LLMs, prompt management, evaluation (evals), safety, and cost awareness. Help integrate monitoring and evaluation tooling (e.g., Arize, LangSmith, LiteLLM etc.) and support secure, policy-aligned deployments.
Support AI/ML pipelines and model lifecycle
Build, maintain, and troubleshoot AI/ML and GenAI pipelines, batch jobs, and workflows using tools such as Composer (Airflow), Vertex AI, Dataproc, Dataflow, and BigQuery etc.
Partner with infrastructure and security teams to incorporate enterprise security tooling into AI/ML workflows (e.g., NexusIQ, StackRox, Wiz etc.).
Help standardize LLMOps patterns using model gateways (e.g., Gemini Enterprise, LiteLLM, or similar) to enable governed model access.
Improve reliability, monitoring, and model quality
Support model/LLM monitoring practices such as drift/quality monitoring, embeddings monitoring, and evaluation (e.g., with Arize or similar).
Implement and maintain logging, alerting, and basic SLOs for AI/ML workloads and pipelines using tools like Splunk, New Relic, and PagerDuty.
Participate in incident response, root-cause analysis, and platform improvements to increase overall reliability and developer experience.
Who You Are
Bachelor’s degree or higher in Computer Science or a related field (or equivalent practical experience).
2+ years of experience in Cloud-native software engineering.
Proficiency in Python (or a similar object-oriented language), with interest in building AI-powered services and tooling.
Working experience with GCP (e.g., Vertex AI, GKE, BigQuery, Composer/Airflow, Dataflow, Dataproc etc.) or another major cloud provider (AWS/Azure).
Familiarity with one or more GenAI patterns and concepts such as RAG pipelines, vector stores, prompt versioning, evaluation, or agent frameworks.
Hands-on familiarity with Kubernetes and containerized deployments (Docker image-based workflows).
Exposure to GitOps or CI/CD workflows (e.g., ArgoCD and/or GitHub Actions).
Experience in supporting production systems: debugging, monitoring, incident response, and continuous improvement.
Eagerness to learn, collaborate, and contribute in a team environment.
Demonstrated alignment with Priceline values: 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 are essential.
Nice-to-haves
Familiarity with enterprise MLOps tooling and best practices.
Basic understanding of infosec practices such as RBAC and security posture management.
Exposure to SRE concepts (e.g., error budgets) for Data and AI/ML systems.
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 $105,000- $125,000K CAD.
Who We Are
WE ARE PRICELINE.
Our success as one of the biggest players in online travel is all thanks to our incredible, dedicated team of talented employees. Priceliners are focused on being the best travel deal makers in the world, motivated by our passion to help everyone experience the moments that matt
About the Company
Priceline, part of Booking Holdings Inc., has been a leader in online travel for over 25 years. Through our innovative technology, we make travel affordable and accessible for all, helping millions of travelers each year experience the moments that matter most. Whether it's a much-needed getaway, wedding, reunion, graduation, or rooting on a favorite team--those are the moments that nobody should miss out on.
We welcome people who are at the top of their game, who want to learn and grow with others and who take their work s...
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