Santiago, Chile · last month
Build Arcadia's software factory components and integrate coding agents and LLM-backed automation into the delivery workflow, with evals and instrumentation. Work remotely from Chile with US overlap hours.
Benefits: • "Remote first" culture - work anywhere in the continental US as long as you have a reliable internet connection • Flexible PTO - no accrued hours and no limit on the number of vacation days exempt employees can take each year • 11 annual holidays • 10 days sick leave • Up to 2 weeks bereavement leave • 2 volunteer days off • 2 professional development days off • Parental Leave Benefits for ALL parents • 75-95% employer cost coverage for medical, dental, and vision benefits for employees and dependents • A supportive engineering culture that values diversity, empathy, teamwork, trust, and efficiency Celebrating Diversity and Inclusion Here at Arcadia, we cultivate diversity, celebrate individuality, and believe unique perspectives are key to our collective success in creating a clean energy future. Arcadia is committed to equal employment opportunities regardless of race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, disability, genetic information, protected veteran status, or any status protected by applicable federal, state, or local law. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation by emailing careers@arcadia.com prior to completing your application. There will also be a competitive benefits and equity (bonus if applicable) component to the package. The exact compensation at which this job is filled will be determined by the skills, experience, and location of the qualified candidate. Please note that we are unable to offer visa sponsorship for this position at this time. Automated Screening: Arcadia uses AI-assisted technology to evaluate candidates on relevant skills, experience, and education as outlined in the job description. Human review is part of all hiring decisions. Candidates may request an alternative selection process by contacting careers@arcadia.com before submitting their application. Data Privacy & California Residents: You voluntarily provide personal information (such as your resume, contact details, and assessment responses) when submitting an application. We may use this to evaluate your candidacy and derive inferences from this data to match your profile with open roles. For California Residents: This collection is consistent with the CCPA. You have the right to request access to or deletion of your data by contacting careers@arcadia.com. *Visa Sponsorship • Select R&D & Data roles: We are proud to offer visa sponsorship opportunities for qualified candidates interested in joining our team • Other roles: Please note that we are unable to offer visa sponsorship for this position at this time BI LINGUAL BOTH WRITTEN AND VERBAL : ENGLISH/SPANISH PLEASE SUBMIT ENGLISH VERSION OF RESUME Who We Are Arcadia is the AI-powered energy intelligence platform for businesses. We replace fragmented tools and manual workflows with one platform to pay utility bills, buy energy, and advance sustainability — across every location, at enterprise scale. Trusted by Fortune 2000 companies, Arcadia combines unified data, AI-powered analytics, and expert advisory to help enterprise teams save money, mitigate risk, and cut carbon. We deliver this through three comprehensive solutions: • Utility Bill Management: Automating the entire utility bill lifecycle — from data capture and validation to payment processing and auditing. • Energy Procurement Advisory: Bringing together comprehensive data, AI-powered analytics, market expertise, and a strong partner network to make sophisticated procurement options accessible to all. . • Sustainability Reporting — Verified emissions data with seamless integration into leading sustainability platforms. Tackling the world's most complex energy challenges requires diverse thinking. We're building teams of people from different backgrounds, industries, and disciplines — united by a belief that energy management should be simple, intelligent, and a genuine driver of business value. What we’re looking for: We are seeking a hands-on software engineer to be the first engineer on the AI Enablement team. This individual will build Arcadia's software factory and convert manual operational processes into automation that reports on its own accuracy. The ideal candidate knows what a healthy delivery pipeline looks like, has shipped and maintained LLM-backed systems in production, builds with coding agents daily, and is comfortable setting patterns where none exist. Models are a dependency here, the way a database is a dependency for a backend engineer. This is not model training or data science. Arcadia is open to fully remote candidates and employees have access to co-working spaces. This role is based in Chile and works United States overlap hours. What you'll do: • Map how code moves from ticket to production at Arcadia today, find where it slows down or breaks, and bring the evidence. • Build and ship Arcadia's software factory components, from scaffolding and templates to the CI patterns that make the fast path the safe path. • Put coding agents into the delivery workflow with the guardrails that keep them from shipping bad code: specs, verifiers, tests, and review norms. • Prototype against the open build-versus-buy question and come back with working evidence. • Convert manual operational processes into instrumented automation, and bring the before-and-after numbers that show it worked. • Instrument everything you ship. You should be able to say what your systems get wrong, how often, what changed and how they can be improved. • Integrate agents and automation with the systems Arcadia runs on: Zendesk, Jira, Confluence, GitHub, and Snowflake. What will help you succeed: Must-haves: You will spend your time building things other people depend on: the templates an engineer reaches for at the start of a project, the automation an operations team stops thinking about because it works. That means understanding their work well enough to see the pattern they cannot see from inside it, and caring enough about their experience to build the version they will actually pick up. • You have shipped LLM-backed systems into production and kept them running. • You write production Python and have kept it running. That means typing, tests across the pyramid, dependency and packaging discipline, and error handling. • You have owned the delivery path, not just worked inside it: branching strategy, code review standards, CI/CD pipelines, release and rollback. • You know how to build good evals: what to measure, how to construct a dataset that exposes real failure modes, when a judge model earns its cost, and what threshold blocks a release. You can name an eval you designed and a failure it caught. • You build with coding agents daily and you have wired them into real workflows, not just an editor. Agent CLIs in scripts and pipelines, model APIs called directly, MCP servers connecting agents to the systems that hold the context. You can show where you intervened, where you let the agent run, and how you keep it from breaking things. • You can reason about cost, latency, and failure modes before you reach for a framework. • You work comfortably in English with colleagues in the United States. Nice-to-haves: • Internal developer tooling or platform work that other engineers adopted. • Java and Spring Boot microservices. • Docker, Kubernetes, and AWS services such as ECS, Lambda, SQS, and S3. • MySQL or another relational database, Snowflake, and dbt. • MCP servers you have authored and run. • LangGraph or comparable agent orchestration in production. • n8n or similar workflow tooling at real volume. • Human-in-the-loop design, permissioning, and audit trails. • Migrating legacy RPA or scripted automation into agent-based architectures.
Posted Oct 5, 2026
