AI Summary
Join our high-performance team to build a platform merging real-time physics, structured knowledge, and autonomous intelligence. Contribute to Core Backend development, focusing on high-performance APIs, system reliability, and rapid delivery. Develop skills in Python, FastAPI, and distributed systems.
Key Highlights
High-performance team
Core Backend development
Python, FastAPI, and distributed systems
Key Responsibilities
Build low-latency Python services (FastAPI) to serve live data to frontend and AI models.
Debug complex concurrency issues and ensure production reliability in distributed systems.
Adopt a 'deliver fast' mentality without compromising on code quality, testing, or API design standards.
Technical Skills Required
Benefits & Perks
Competitive compensation
Fully remote position
Nice 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
Job Description
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.
Job Duties
We are building a platform that merges real-time physics, structured knowledge, and autonomous intelligence. We are looking for developers ready to tackle one (or more) of those challenges:
- Ingestion: Handling massive streams of sensor data with minimal latency.
- Intelligence: Making LLMs deterministic and reliable within robust multi-agent systems.
- Context: Modeling complex ontologies to map thousands of physical assets.
You will join a high-performance team, contributing to the Core Backend while focusing on one of the following distinct tracks:
Core Responsibilities
- High-Performance APIs: Build low-latency Python services (FastAPI) to serve live data to frontend and AI models.
- System Reliability: Debug complex concurrency issues and ensure production reliability in distributed systems.
- Rapid Delivery: Adopt a “deliver fast” mentality without compromising on code quality, testing, or API design standards.
Streaming & High-Throughput Data
- Build Streaming Pipelines: Design scalable services using Kafka and Spark/Flink to process raw sensor data in real-time.
- Time-Series Optimization: Optimize database schemas (TimescaleDB) to enable fast historical data retrieval and implement algorithmic checks to validate sensor readings.
- Build Autonomous Agents: Deploy stateful agents (using LangGraph) that plan tasks, query Knowledge Graphs, and execute tools without hallucinating.
- Advanced RAG: Build Graph-RAG pipelines that combine semantic search with structured knowledge traversal for grounded answers
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- Knowledge Graph Engineering: Design domain ontologies in Neo4j, defining relationships between assets, documents, and time-series data.
- Search Infrastructure: Implement Hybrid Retrieval logic combining Vector Search, Full-Text Search, and Graph traversal.
Must Haves:
- Complete Bachelor's degree in Computer Science, Engineering, or related.
- 5+ years of experience in Python Backend development.
- Advanced English communication skills.
- Computer Science fundamentals: Data Structures and Algorithms.
- Strong experience building and documenting REST APIs (FastAPI).
- 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
- 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.
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We use a modern, high-performance stack. You should be proficient in the Core and deeply knowledgeable in your chosen track.
- Core Backend: Python 3.12+ (FastAPI, Pydantic), Polars, Docker, Kubernetes.
- Streaming: Apache Kafka, Flink, Spark Streaming, TimescaleDB, Tiger Data.
- GenAI: LangGraph, LangChain, LiteLLM, Azure OpenAI/Anthropic/Local SLMs.
- Graph/Data: Neo4j (Cypher), PostgreSQL (pg_vector, Full-Text Search).
- Problem Solver: You dig into logs to find the root cause of a data spike, a silent failure, or a disconnected node in a graph.
- Modern Pythonista: You are up-to-date with modern Python async patterns and typing, ensuring code is high-performance and maintainable.
- You understand Big O notation and how to optimize code for CPU/memory efficiency.
Location
Fully remote position.
Job Details
Requisition Number: 205554
Experience Level: Entry-Level
Job Family: Engineering/Science/Technology
Product Service Line: Landmark Software & Services
Full Time / Part Time: Full Time
Employee Group: Temporary
Compensation Information
Compensation is competitive and commensurate with experience.
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