Software Engineer, Cloud Infrastructure

Responsibilities

• Design, provision, and maintain AWS infrastructure using infrastructure-as-code tools such as AWS CDK or Terraform.
• Build CI/CD and testing for applications, infrastructure, and ML pipelines with GitHub Actions, CodeBuild, and CodePipeline.
• Operate secure networking with VPCs, PrivateLink, and VPC endpoints; manage IAM, KMS, Secrets Manager, and audit logging.
• Deploy and operate model endpoints using AWS Bedrock and/or SageMaker, selecting appropriate compute services for inference workloads.
• Build application services that call LLMs through clean APIs, including streaming, batching, and backoff strategies.
• Implement prompt and tool execution flows with LangChain or similar frameworks.
• Design chunking, embedding, ingestion, and retrieval pipelines for documents, time series, and multimedia data.
• Operate vector search systems and tune recall, latency, and cost.
• Build knowledge bases and data synchronization from S3, Aurora, DynamoDB, and external sources.
• Create evaluation harnesses and monitor quality, latency, regressions, model telemetry, token usage, and costs.
• Implement guardrails, rate limits, fallbacks, provider routing, PII detection, redaction, access controls, and audit trails.
• Build ingestion and processing pipelines with data integrity, lineage, and cataloging.
• Manage infrastructure supporting edge devices, secure messaging, identity, and over-the-air updates.
• Support application and product teams integrating retrieval services, embeddings, and LLM chains.
• Optimize retrieval, caching, inference, model selection, quantization, instance selection, and autoscaling.
• Own work from design through production, including on-call and continuous improvement.

Requirements

• Production experience shipping or operating LLM-powered applications.
• Strong AWS experience, including VPC, IAM, KMS, CloudWatch, S3, ECS/EKS, Lambda, Step Functions, Bedrock, and SageMaker.
• Experience with RAG design, prompt versioning, and chain orchestration using LangChain or similar tools.
• Experience building ingestion and transformation pipelines in Python.
• Familiarity with Glue, Athena, EventBridge, and SQS.
• Understanding of least privilege, secrets management, network isolation, and compliance for sensitive data.
• Experience using quantitative evaluations, A/B testing, and live metrics.
• Strong communication skills and ability to explain technical tradeoffs across product, security, and application engineering.

Nice-to-Haves

• 4+ years working with serverless or container platforms on AWS.
• Experience with vector databases, OpenSearch, or pgvector at scale.
• Experience 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.
• Aviation data or other safety-critical domain experience.
• DevOps or DevSecOps experience automating CI/CD for ML and application services.

Compensation and Benefits

• Annual salary: $135,000–$260,000.
• 100% of employee medical premiums covered and 25% of dependent premiums covered.
• Three weeks of paid time off and 13+ paid company holidays.
• 401(k) offered.