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 Opportunity

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.

What You'll Do

You will join a high-performance team, contributing to designing and delivering Advanced Agentic AI Systems across the full stack — from data pipelines and knowledge graphs, through agent orchestration, to the interactive UI engineers and analysts use every day.

Core Responsibilities

GenAI & Autonomous Agents

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.
Build agents capable of integrating with engineering tools, simulators, databases, and knowledge sources.
Collaborate with domain experts to align agent behavior with technical expectations and constraints.
Implement safeguards to ensure accuracy, traceability, and reliability of AI-generated outputs.
Continuously optimize prompting, agent orchestration, and performance under real-world conditions.
High-Performance APIs: Build low-latency Python services (FastAPI) to serve live data to frontend and AI models.
Rapid Delivery: Adopt a “deliver fast” mentality without compromising code quality, testing, or API design standards.

Full-Stack & Visualization

Build interactive React-based AI chat assistant including canvas/dashboard views

Technology Stack & Desired Profile

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:

GenAI: LangGraph, LangChain, LiteLLM, Azure OpenAI/Anthropic/Local SLMs, MCP (Model Context Protocol).
Backend: Python 3.12+ (FastAPI), Kafka, Neo4j.
Frontend: React, Angular 16+, TypeScript, RxJS, Plotly.js.
Data: Apache Airflow, Trino, Apache Iceberg, MinIO, Delta Lake, Polars/Spark.
Infrastructure: Kubernetes (EKS/AKS/K3s/on-prem), Terraform, Hybrid Cloud.

Desired Profile

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.
Full-Stack Mindset: You move comfortably between backend services, agent orchestration, and frontend UI work, and can reason about trade-offs across the whole stack.

Qualifications

Must Haves:

GenAI: Practical experience building applications with LLMs, Agentic Frameworks (LangGraph), and Vector Databases.
5+ years of experience in Python Backend development.
2+ years of experience with modern frontend frameworks (React and/or Angular) and TypeScript.
Advanced English communication skills.
Computer Science fundamentals: Data Structures and Algorithms.
Strong experience building and documenting REST APIs (FastAPI).

Good to Have:

Agent Evaluation: Experience building eval pipelines for agentic systems (e.g., Lang Smith, Ragas, or custom harnesses) to test task success, groundedness, and hallucination rate.
Streaming: Proficiency with Streaming Technologies (Kafka, Flink, Spark) and Time-Series Databases (TimescaleDB, InfluxDB).
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.

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: 209785
Experience Level: Mid to 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.

Originally posted on Himalayas

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