We are looking for the right people — people who want to innovate, achieve, grow and lead. We attract and retain the best talent by investing in our employees and empowering them to develop themselves and their careers. Experience the challenges, rewards and opportunity of working for one of the world’s largest providers of products and services to the global energy industry.
The Oportunity
We are building a platform that merges real-time physics, structured knowledge, and autonomous intelligence. You will be the technical anchor for a team of Senior Engineers handling:
- Backend: Ingesting massive sensor streams and running multi-agent AI systems.
- Data: Organizing tons of industrial data into a Medallion Architecture.
- Frontend: Building the "Control Room" and complex AI interfaces.
- DevOps: Deploying across hybrid cloud (AWS/Azure) and edge (K3s) environments.
Your challenge is to ensure these distinct pieces fit together. ensuring the backend model is consumable by the frontend’s "Visualizations" and that the "Data Pipelines" are reliably deployed by DevOps.
Job Duties
- Technical Orchestration: You will drive cross-boundary architectural decisions. You will decide how the Backend serves live telemetry to Frontend dashboards and how Data Engineering pipelines feed the Knowledge Graph .
- Code & Quality Standards: Enforce high standards across the stack. You will review API designs (FastAPI), ensure the Frontend maintains strict Component Architecture, and verify that Data pipelines implement appropriate quality gates.
- The "Expert": When the DevOps engineer faces a connectivity issue between Cloud and On-Prem, or the Backend engineer struggles with concurrency in a distributed stream, you are the senior voice in the room, guiding the solution.
- Team Leadership: Conduct code reviews, mentor senior developers, and translating high-level product requirements into technical tasks (ADO) for the squad.
The Technology Stack
You do not need to be an expert in every single tool, but you must be able to discuss technical trade-offs across the entire stack:
- Backend: Python 3.12+ (FastAPI), Kafka, Neo4j, LangGraph.
- Frontend: React, Angular 16+, TypeScript, RxJS, Plotly.js.
- Data: Apache Airflow, Delta Lake, Polars/Spark.
- Infrastructure: Kubernetes (EKS/AKS/K3s), Terraform, Hybrid Cloud
Desired Profile
- The Architect-Implementer: You can draw the system architecture on a whiteboard, but you are not afraid to open an IDE to debug a failing pipeline or a slow query.
- The Polyglot: You are likely a Backend or Full-Stack native, but you understand the complexity of Frontend state management (NgRx/Signals) and the constraints of Medallion Data Architectures.
- Reliability Mindset: You understand that we are dealing wi