AI Engineer II - Blue Ring

BLUE ORIGIN • Reston, WA

1d • Onsite

About The Position

At Blue Origin, we envision millions of people living and working in space for the benefit of Earth. We’re working to develop reusable, safe, and low-cost space vehicles and systems within a culture of safety, collaboration, and inclusion. Join our team of problem solvers as we add new chapters to the history of spaceflight! The role is part of the In-Space Systems business unit, which is focused on addressing two of the most compelling challenges in spaceflight today: space infrastructure and increasing mobility on-orbit. Blue Ring is Blue Origin's multi-mission space mobility platform, and this team is building the next generation of intelligent ground systems that will redefine how satellite fleets are operated—moving beyond manual monitoring and reactive processes. We are seeking an AI Engineer II to join the Blue Ring software team. You will contribute to the AI and machine learning capabilities embedded in Blue Ring's ground system, spanning multi-agent monitoring, conversational knowledge retrieval, and ML-driven anomaly detection that empower satellite operations at fleet scale. In this role, you will help build agent tooling, maintain RAG knowledge pipelines, develop telemetry ML models, and support production AI services that operators rely on daily.

Requirements

• Able to work onsite in one of our Kent, WA, Renton, WA, or Reston, VA offices.
• Bachelor's degree in Computer Science, Machine Learning, Electrical Engineering, or a related field
• 3+ years of professional software development experience with exposure to AI/ML applications
• Proficiency in Python and familiarity with at least one AI/ML framework (PyTorch, TensorFlow)
• Experience with building or contributing to LLM-based applications, RAG pipelines, or agent-based systems
• Exposure to time-series data processing, anomaly detection, or ML model training on sensor or telemetry data
• Experience with cloud platforms (AWS preferred), containerization (Docker), and basic CI/CD practices
• Solid understanding of CS fundamentals: data structures, algorithms, object-oriented design, and version control
• Strong analytical and problem-solving skills with attention to detail
• Good written and verbal communication skills for documentation and team collaboration

Nice To Haves

• Experience with AWS Bedrock, SageMaker, or equivalent managed AI/ML services
• Experience with Databricks or similar platforms for data engineering and ML workflows
• Familiarity with vector databases (e.g., Pinecone, pgvector, FAISS) and embedding model pipelines
• Experience with time-series ML architectures (RNNs, LSTMs, Transformers) for forecasting or anomaly detection
• Exposure to multi-agent system frameworks or agentic AI orchestration patterns
• Familiarity with spacecraft operations, satellite telemetry, or aerospace engineering concepts
• Experience with infrastructure-as-code tools (Terraform) and Kubernetes
• Experience with real-time data streaming systems (Kafka, Kinesis)
• Familiarity with reinforcement learning concepts or graph neural network applications
• Interest or experience in model compression, edge deployment, or resource-constrained inference

Responsibilities

• Multi-Agent System Development: Implement and test agent components within the multi-agent architecture for telemetry analysis, anomaly detection, and reporting
• Build and maintain integrations that connect agents to ground system services
• Develop agent tooling, prompt templates, and orchestration logic for LLM service integrations
• Build and maintain RAG pipeline components including document ingestion, embedding generation, and vector database indexing
• Implement retrieval strategies and answer generation workflows for operator queries
• Implement components for human-in-the-loop decision workflows, including investigation packages and remediation options
• Deploy and maintain containerized AI services using Docker and AWS infrastructure
• Contribute to audit trail, observability systems, and production operations including incident response
• Model Development (Post-training and Time-series Analysis): Prepare and transform spacecraft telemetry data for ML model training
• Assist in training and evaluating anomaly detection and time-series forecasting models on telemetry data
• Support automated model retraining pipelines that incorporate new flight data and operator feedback
• Develop model evaluation scripts and metrics tracking

Benefits

• Medical, dental, vision, basic and supplemental life insurance, paid parental leave, short and long-term disability, 401(k) with a company match of up to 5%, and an Education Support Program.
• Paid Time Off: Up to four (4) weeks per year based on weekly scheduled hours, and up to 14 company-paid holidays.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level