Beacon Venture Capital

Software Engineer, Cloud Infrastructure

Beacon Venture Capital

full-time

Posted on:

Origin:  • 🇺🇸 United States • California

Visit company website
✨ AI Apply
Manual Apply

Salary

💰 $130,000 - $225,000 per year

Job Level

Mid-LevelSenior

Tech Stack

AirflowAWSCloudDynamoDBIoTPostgresPythonRedisTerraform

About the role

  • 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.
  • 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.
  • 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. Tune recall, latency, and cost.
  • Build and maintain knowledge bases and data syncs from S3, Aurora, DynamoDB, and external sources.
  • Create offline and online eval harnesses for prompts, retrievers, and chains. Track quality, latency, and regression risk.
  • 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.
  • Implement PII detection and redaction, access controls, content filters, and human-in-the-loop review where needed.
  • Use Bedrock Guardrails or policy services to enforce safety standards. Maintain audit trails for regulated environments.
  • 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.
  • Manage infrastructure that deploys to and communicates with edge devices. Support secure messaging, identity, and over-the-air updates.
  • 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.
  • Tune retrieval quality, context window use, and caching with Redis or Bedrock Knowledge Bases.
  • Optimize inference with model selection, quantization where applicable, GPU/CPU instance choices, and autoscaling strategies.

Requirements

  • 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.