Software Engineer, Cloud Infrastructure

Key Responsibilities

Cloud Infrastructure Setup and Maintenance

• Design, provision, and maintain AWS infrastructure using IaC tools such as AWS CDK or Terraform
• Build CI/CD and testing for apps, infra, and ML pipelines using GitHub Actions, CodeBuild, and CodePipeline
• Operate secure networking with VPCs, PrivateLink, and VPC endpoints
• Manage IAM, KMS, Secrets Manager, and audit logging

LLM Platform and Runtime

• Stand up and operate model endpoints using AWS Bedrock and/or SageMaker; evaluate when to use ECS/EKS, Lambda, or Batch for inference jobs
• Build and maintain application services that call LLMs through clean APIs, with streaming, batching, and backoff strategies
• Implement prompt and tool execution flows with LangChain or similar, including agent tools and function calling

RAG Data Systems and Vector Search

• Design chunking and embedding pipelines for documents, time series, and multimedia; orchestrate with Step Functions or Airflow
• Operate vector search using OpenSearch Serverless, Aurora PostgreSQL with pgvector, or Pinecone
• Build and maintain knowledge bases and data syncs from S3, Aurora, DynamoDB, and external sources

Evaluation, Observability, and Cost Governance

• Create offline and online eval harnesses for prompts, retrievers, and chains
• Instrument model and app telemetry with CloudWatch and OpenTelemetry
• Build token usage and cost dashboards with budgets and alerts
• Add guardrails, rate limits, fallbacks, and provider routing for resilience

Safety, Privacy, and Compliance

• Implement PII detection and redaction, access controls, content filters, and human-in-the-loop review
• Use Bedrock Guardrails or policy services to enforce safety standards
• Maintain audit trails for regulated environments

Data Pipeline Construction

• Build ingestion and processing pipelines for structured, unstructured, and multimedia data
• Ensure integrity, lineage, and cataloging with Glue and Lake Formation
• Optimize bulk data movement and storage in S3, Glacier, and tiered storage; use Athena for ad-hoc analysis

IoT Deployment Management

• Manage infrastructure that deploys to and communicates with edge devices
• Support secure messaging, identity, and over-the-air updates

Analytics and Application Support

• Partner with product and application teams to integrate retrieval services, embeddings, and LLM chains into user-facing features
• Provide expert troubleshooting for cloud and ML services with an emphasis on uptime and performance

Performance Optimization

• Tune retrieval quality, context window use, and caching with Redis or Bedrock Knowledge Bases
• Optimize inference with model selection, quantization, GPU/CPU instance choices, and autoscaling strategies

What Will Make You Successful

• End-to-End Ownership: Drives work from design through production, including on-call and continuous improvement
• LLM Systems Experience: Shipped or operated LLM-powered applications in production; familiar with RAG design, prompt versioning, and chain orchestration using LangChain or similar
• AWS Depth: Strong with core AWS services such as VPC, IAM, KMS, CloudWatch, S3, ECS/EKS, Lambda, Step Functions, Bedrock, and SageMaker
• Data Engineering Skills: Comfortable building ingestion and transformation pipelines in Python; familiar with Glue, Athena, and event-driven patterns using EventBridge and SQS
• Security Mindset: Applies least privilege, secrets management, network isolation, and compliance practices appropriate to sensitive data
• Evaluation and Metrics: Uses quantitative evals, A/B testing, and live metrics to guide improvements
• Clear Communication: 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

Perks & Benefits (Full-Time Employees)

• Healthcare: 100% of employee medical premiums covered; 25% for dependents
• Time Off: 3 weeks PTO plus 13+ paid company holidays
• Stipends: Monthly phone and wellness benefits
• 401(k): Offered (no current employer match, but committed to enhancing this benefit)