Remote Observability Engineer Jobs in Portland, OR

Location: Portland, OR (Hybrid three days in office)
Remote considered for exceptional candidates

Vacatia is building the future of timeshare and vacation ownership. We operate in a fragmented, operationally complex industry, and we believe AI is the lever that allows a small, high-performing team to fundamentally reshape how the business operates.

The problems here are real and consequential owner mortgage outcomes, rental revenue optimization, contact center intelligence, and operational decision-making across dozens of resorts all powered by data that has historically been underutilized and poorly connected.

Were launching a brand-new AI engineering function focused on building the foundational operating layer for every AI initiative at Vacatia: agent infrastructure, evaluation and observability systems, integrations across customer-facing platforms, and the data pipelines that make intelligent workflows possible.

This is true zero-to-one platform building work. No existing AI stack. No inherited patterns. No predetermined tooling. Youll help define all of it.

• Build foundational AI infrastructure from the ground up with significant architectural ownership
• Shape the long-term AI strategy for an entire business
• Work on meaningful operational and customer-impact problems not experimental side projects
• Operate with executive-level visibility and support for AI investment
• Influence the engineering culture, standards, and technical direction of a growing team
• Join early enough to meaningfully define the platform, practices, and roadmap
• Receive equity participation through stock options as part of total compensation

As the founding engineer for this initiative and the senior-most individual contributor on the team, youll architect and operationalize the systems that power every AI workflow at Vacatia.

Youll own:

• Define the technical strategy and foundational stack for AI systems at Vacatia
• Evaluate and select runtimes, orchestration patterns, agent frameworks, model providers, and observability tooling
• Lead critical build-vs-buy and vendor evaluation decisions

• Design the runtime, orchestration, deployment, and CI/CD patterns for AI agents
• Establish prompt, tool, and workflow versioning strategies
• Build scalable deployment pipelines that support safe iteration and production reliability

• Build evaluation harnesses, regression testing systems, replay tooling, and operational QA frameworks
• Define measurable standards for agent performance and production reliability
• Create systems that enable rapid experimentation without sacrificing quality

• Implement tracing, structured logging, telemetry, and dashboarding across AI workflows
• Develop operational visibility into agent behavior, performance, and failure modes
• Ensure outcomes are measurable and tied to business impact

• Build production integrations across Salesforce, AWS Connect, internal platforms, and customer support systems
• Create data transformation and ingestion pipelines for transcripts, recordings, operational data, and documents
• Develop the infrastructure that allows AI systems to interact effectively with real business operations

• Establish engineering standards, architecture patterns, and operational discipline
• Mentor future engineers joining the team
• Contribute to hiring, onboarding, and technical growth as the organization scales

Youll partner closely with Product, Engineering Leadership, and Vacatias broader AI transformation initiatives to define how AI systems are built and operationalized across the company.

• 10+ years of backend or full-stack engineering experience building and operating production systems at scale
• Deep, hands-on experience designing and deploying LLM-powered or agentic systems in production environments
• Strong architectural judgment across AI systems, backend infrastructure, and distributed integrations
• Expertise with REST APIs, webhooks, event-driven architectures, queues, retry patterns, and idempotent systems
• Strong familiarity with modern AI model ecosystems, including frontier and open-weight models
• Experience designing evaluation frameworks, observability systems, and operational measurement practices for AI workflows
• Proven technical leadership experience through architecture ownership, mentorship, and long-term systems design
• Strong software engineering fundamentals including testing, deployment hygiene, reliability, and operational ownership

• Production experience with multiple agent frameworks and orchestration approaches
• Experience evaluating and implementing AI observability and evaluation tooling
• Experience working with messy operational datasets including transcripts, support interactions, and semi-structured logs
• Experience serving as the senior-most IC on a growing engineering team

• Familiarity with Salesforce AI products and Service Cloud Voice
• Experience with AWS Connect or contact center technologies
• Background supporting customer experience or operations organizations
• Open-source contributions, conference speaking, or technical writing in the AI space

This is an opportunity to define the AI foundation for an entire company at the moment the investment and urgency are real. If you enjoy solving operationally messy, technically complex problems and want ownership over the systems, patterns, and standards that shape what comes next wed love to hear from you.