Full Stack Engineer, Forward Deployed (AI)

Location: Houston, United States; hybrid. Travel to customer environments is required, including cloud, on-premise, hybrid, and air-gapped infrastructure.

Company

hirify.global is an AI company building Orbital, a physics-informed foundation model for energy operations across oil and gas, refineries, and petrochemicals.

What you will do

• Deploy, configure, customise, upgrade, and operationalise Orbital full-stack applications in customer environments.
• Build and adapt real-time dashboards, anomaly-monitoring interfaces, chat interfaces, and WebSocket pipelines for live AI model outputs.
• Deploy and extend FastAPI microservices and REST and GraphQL APIs, integrating customer business logic, ML inference endpoints, and data services.
• Integrate SSO, SAML, OAuth, role-based access controls, tenant isolation, firewalls, networking, and enterprise security requirements.
• Manage PostgreSQL schemas, Alembic migrations, Kubernetes, Helm, Docker, Terraform/Terragrunt, and GitHub Actions deployments.
• Configure observability with Grafana and Prometheus, troubleshoot production incidents, and deliver customer-specific extensions and operational handovers.

Requirements

• Strong proficiency in JavaScript and TypeScript with React and Node.
• Experience with backend frameworks including FastAPI, Express, or Django, plus solid Python for scripting, APIs, and data integration.
• Experience building containerised microservices with Docker and Kubernetes.
• Working knowledge of Kafka or RabbitMQ, PostgreSQL, and Linux deployment, debugging, and performance tuning.
• Strong production troubleshooting skills and the ability to work directly with customer IT, OT, data, and engineering teams.
• Ability to work in a hybrid setup in Houston and travel to customer sites is required.

Nice to have

• Exposure to time-series or industrial data and operator-facing dashboards.
• Experience as a software engineer in oil and gas or energy environments.

Culture & Benefits

• Work in cross-functional pods of three with ML/AI Engineers and Data Engineers.
• Each pod delivers multiple customer deployments per quarter.
• Work directly with industrial operators, APC engineers, technologists, and enterprise engineering teams.
• Build systems used in control rooms, engineering offices, and operational environments.