Brazil - Remote: Full Stack AI Developer
At a glance
Mid-level AI Engineering role at Halliburton. Remote, Brazil.
Pay not stated AI Engineering salary
aimlroles summary, based on the employer's posting.
What you'll do
- Shape how telemetry reaches dashboards and how data pipelines supply the knowledge graph
- Set technical direction across backend, frontend, data and infrastructure, keeping their interfaces aligned
- Review API designs, frontend structure and pipeline quality checks across the stack
- Guide engineers through distributed-stream concurrency and cloud-to-site connectivity problems
- Review code, coach senior developers and turn product needs into squad tasks
What you bring
- At least ten years in software engineering, including two years or more leading technical teams
- Strong Python backend skills and a solid grasp of single-page frontend architecture and asynchronous data loading
- Experience designing or managing data-heavy systems using ETL, streams or data lakes
- Working knowledge of Docker, Kubernetes and CI/CD, plus advanced English communication skills
Who this fits
This role suits a hands-on technical leader who can make architecture decisions and still debug pipelines or slow queries. It is fully remote in Brazil and is listed at mid, senior or principal experience levels.
From the employer
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.
About the Role
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:
- AI: Architect and develop a multi-agent AI framework where autonomous agents coordinate to solve domain-specific technical queries.
- 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.
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 with critical industrial environments. You prioritize testing, validation, and security.
Qualifications
Must Haves:
- 10+ years of experience in Software Engineering, with at least 2+ years leading technical teams.
- Deep proficiency in Python Backend Development.
- Solid understanding of Frontend complexity (SPA architecture, async data loading).
- Experience designing or managing Data Intensive Applications (understanding ETL, Streams, or Data Lakes).
- Familiarity with DevOps/Cloud concepts (Docker, Kubernetes, CI/CD).
- Advanced English communication skills.
Good to Have:
- Streaming: Proficiency with Streaming Technologies (Kafka, Flink, Spark) and Time-Series Databases (TimescaleDB, InfluxDB).
- GenAI: Practical experience building applications with LLMs, Agentic Frameworks (LangGraph), and Vector Databases.
- Graph: Hands-on experience with Graph Databases (Neo4j/Cypher), SQL database design, and Hybrid Search strategies
- Experience with Digital Twins, IoT, or Industrial Data.
- Experience with GenAI/LLM architecture (RAG, Agents).
- Background in Heavy Industry, O&G, or IoT data (MQTT, OPC UA).
- Experience with Local LLMs (Ollama) for privacy-focused deployments.
- Familiarity with Data Lineage or Metadata management.
Halliburton is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, disability, genetic information, pregnancy, citizenship, marital status, sex/gender, sexual preference/ orientation, gender identity, age, veteran status, national origin, or any other status protected by law or regulation.
Location
Fully remote position.
Job Details
Requisition Number: 209782
Experience Level: Mid-level, Senior or Principal.
Job Family: Engineering/Science/Technology
Product Service Line: Landmark Software & Services
Full Time / Part Time: Full Time
Compensation Information
Compensation is competitive and commensurate with experience.