Full Stack Engineer, Forward Deployed

Applied Computing•Houston, TX

3d•Hybrid

About The Position

Applied Computing was founded in 2023 to build Orbital, a physics-informed foundation model for energy operations. We’re live across oil and gas, refineries, and petrochemicals, working towards our mission: sustainable abundance for a growing planet. The hydrocarbon industry keeps the world running. But its complexity has left operators tied to legacy systems, making critical decisions on less than 10% of available data. We built Orbital to change that. It’s a foundation model built specifically for energy that lets companies use AI at scale, harnessing all of their operational data and optimising in real time for any metric. Decisions get faster, operations get safer, and carbon intensity falls. We’ve raised over $32 million, including one of the largest seed rounds for an AI company in the UK. We’re just getting started. As a Forward Deployed Full Stack Engineer, your job is to make Orbital work in the real world. You will deploy, configure, customise, and operationalise Orbital’s applications inside customer environments, spanning cloud, on-premise, hybrid, and air-gapped infrastructure. You are not building generic platform features for abstraction. You are ensuring Orbital is usable, integrated, secure, and production-ready inside complex enterprise ecosystems. You’ll work directly with customer IT, OT, data, and engineering teams adapting interfaces, extending APIs, integrating identity systems, and troubleshooting deployments live in production. Operating Context: Forward Deployed Engineers operate in pods of three alongside ML / AI Engineers and Data Engineers. Each pod delivers 2–3 customer deployments per quarter, owning application deployment, integration, customisation, and operational reliability. You will be required to travel.

Requirements

Strong proficiency in JavaScript/TypeScript (React, Node.js) and back-end frameworks (FastAPI, Express, Django).
Solid working knowledge of Python for scripting, APIs, and data integration.
Experience building containerised microservices (Docker, Kubernetes).
Familiarity with message brokers (Kafka, RabbitMQ).
Familiarity working with databases like PostgresSQL etc.
Proficiency with Linux environments (deployment, debugging, performance tuning).
Strong troubleshooting mindset in production systems.

Nice To Haves

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

Responsibilities

Deploy Orbital’s full-stack applications into customer environments (cloud, on-prem, hybrid).
Configure customer-specific application environments, networking, and access layers.
Customise UI components, workflows, and feature configurations per customer use case.
Implement customer branding, report templates, and UX adaptations.
Ensure applications remain usable in control rooms, engineering offices, and operational settings.
Develop real-time streaming in collaboration with frontend engineer (in Svelte / SvelteKit) dashboards for AI inference and anomaly monitoring.
Implement chat interfaces integrated with LLM services.
Configure WebSocket pipelines for live model outputs.
Adapt UI/UX for industrial workflows (operators, APC engineers, technologists).
Deploy and extend FastAPI microservices.
Configure and customise REST and GraphQL (Strawberry) APIs.
Implement customer-specific business logic and integrations.
Connect application services to ML inference endpoints and data services.
Extend APIs when customer systems require bespoke contracts.
Integrate Orbital with customer identity providers: SSO, SAML, OAuth.
Implement role-based access controls.
Configure tenant isolation and enterprise security requirements.
Work with customer IT to satisfy firewall, network, and compliance constraints.
Deploy and manage PostgreSQL schemas.
Run Alembic migrations across environments.
Optimise queries for production performance.
Configure customer-specific schema mappings where required.
Own application deployment infrastructure: Kubernetes, Helm charts, Docker services.
Manage application-level Terraform / Terragrunt provisioning.
Configure CI/CD pipelines (GitHub Actions).
Deploy services via container orchestration.
Troubleshoot scaling, ingress, and service routing issues.
Configure application monitoring via Grafana dashboards.
Implement logging, alerting, and SLA monitoring.
Support Prometheus metrics integrations.
Debug production incidents in customer environments.
Work directly with customer IT / OT / Engineering teams.
Deploy into air-gapped and tightly firewalled networks.
Troubleshoot infrastructure, networking, and application failures.
Build customer-specific extensions when core product configs are insufficient.
Support onboarding, upgrades, and operational handover.