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Beacon AI
San Carlos, California, United States
Source: Beacon AI careers · View original posting
From Beacon AI's posting. “We” and “our” refer to the employer.
We’re a fast-moving team of aviators, engineers, and operators building an AI platform to make flying safer, more efficient, and more capable. Backed by top investors, we’ve secured a dozen Department of Defense contracts and partnered with major airlines to deliver mission-critical systems. We operate without silos or heavy processes. Small, focused teams own what they build, ship quickly, and learn fast, pushing the boundaries of how humans and AI work together in aviation.
Role Overview
We are seeking skilled Cloud and ML Infrastructure Engineers to lead the buildout of our AWS foundation and our LLM platform. You will design, implement, and operate services that are scalable, reliable, and secure.
The broad scope means focus areas in LLM/ML Infra and IoT infra are strong bonus points. For ML Infra, build the stack that powers retrieval-augmented generation and application workflows built with frameworks like LangChain. Experience with IoT AWS services is a plus.
You will work closely with other engineers and product management. The ideal candidate is hands-on, comfortable with ambiguity, and excited to build from first principles.
Drives work from design through production, including on-call and continuous improvement.
Shipped or operated LLM-powered applications in production. Familiar with RAG design, prompt versioning, and chain orchestration using LangChain or similar.
Strong with core AWS services such as VPC, IAM, KMS, CloudWatch, S3, ECS/EKS, Lambda, Step Functions, Bedrock, and SageMaker.
Comfortable building ingestion and transformation pipelines in Python. Familiar with Glue, Athena, and event-driven patterns using EventBridge and SQS.
Applies least privilege, secrets management, network isolation, and compliance practices appropriate to sensitive data.
Uses quantitative evals, A/B testing, and live metrics to guide improvements.
Explains tradeoffs and aligns partners across product, security, and application engineering.
Bonus Points
4+ years working with serverless or container platforms on AWS.
Experience with vector databases, OpenSearch, or pgvector at scale.
Hands-on with Bedrock Guardrails, Knowledge Bases, or custom policy engines.
Familiarity with GPU workloads, Triton Inference Server, or TensorRT-LLM.
Experience with big data tools for large-scale processing and search.
Background in aviation data or other safety-critical domains.
DevOps or DevSecOps experience automating CI/CD for ML and app services.
Work Location
This is a hybrid role based in San Carlos, CA, with 3+ days per week onsite and the option to work remotely on remaining days.
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