Associate AI​/ML Developer

Overview

Associate AI/ML Developer

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

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.

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.

• Build and maintain Python OOPS (object-oriented programming) services/frameworks and internal AI/ML platform tooling deployed to GKE with Git Ops-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., Lang Chain/Lang Graph/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, Lang Smith, LiteLLM etc.) and support secure, policy-aligned deployments.

• Build, maintain, and troubleshoot AI/ML and GenAI pipelines, batch jobs, and workflows using tools such as Composer (Airflow), Vertex AI, Dataproc, Dataflow, and Big Query etc.

• Partner with infrastructure and security teams to incorporate enterprise security tooling into AI/ML workflows (e.g., Nexus
  
  IQ, Stack Rox, Wiz etc.).

• Help standardize LLMOps patterns using model gateways (e.g., Gemini Enterprise, LiteLLM, or similar) to enable governed model access.

• 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 Pager Duty.

• Participate in incident response, root-cause analysis, and platform improvements to increase overall reliability and developer experience.

• 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, Big Query, 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 Git Ops or CI/CD workflows (e.g., ArgoCD and/or Git Hub 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.

• Familiarity with enterprise MLOps tooling and best practices.

• Basic understanding of infosec practices such as RBAC and…