Software Engineer

Role overview

Join Beacon AI as a Software Engineer specializing in Cloud and ML Infrastructure. You will lead the buildout of the company’s AWS foundation and LLM platform, designing, implementing, and operating secure, scalable services.

Key responsibilities

• Own work end-to-end: from design through production, including monitoring, continuous improvement, and on-call.
• Build and operate AWS infrastructure for cloud and ML services.
• Create CI/CD and testing pipelines for application services (including ML services).
• Operate secure networking and apply security best practices across services.
• Troubleshoot cloud and ML systems in collaboration with other engineers and product management.
• Integrate LLM capabilities into user-facing features, including retrieval, embeddings, and LLM chains/orchestration.
• Use evaluation and metrics (quantitative evals, A/B testing, and live metrics) to guide improvements.

Requirements

• Hands-on and comfortable with ambiguity; excited to build from first principles.
• Strong AWS depth across services such as:
  • VPC, IAM, KMS, CloudWatch, S3
  • ECS/EKS, Lambda, Step Functions
  • Bedrock and SageMaker
• LLM systems experience shipping or operating LLM-powered applications in production, including:
  • RAG design
  • Prompt versioning
  • Chain orchestration using LangChain (or similar)
• Security mindset: least privilege, secrets management, network isolation, compliance practices for sensitive data.
• Data engineering skills with Python for ingestion and transformation pipelines.
  • Familiar with Glue, Athena
  • Event-driven patterns using EventBridge and SQS
• Experience with vector databases / search at scale (e.g., OpenSearch or pgvector).
• 4+ years working with serverless or container platforms on AWS.

Nice to have

• Familiarity with GPU workloads and tools such as Triton Inference Server or TensorRT-LLM.
• Hands-on with Bedrock Guardrails, Knowledge Bases, or custom policy engines.
• Experience with big data tools for large-scale processing and search.
• Background in aviation data or other safety-critical domains.
• DevOps/DevSecOps experience automating CI/CD for ML and application services.