# Software Engineer, Cloud Infrastructure

**Company:** [Beacon AI](https://hotfix.jobs/companies/beacon-ai)
**Location:** San Carlos, CA
**Role:** DevOps / SRE
**Salary:** $135k – $260k/yr
**Skills:** AWS, Aws Cdk, Terraform, GitHub Actions, Kubernetes, Docker, LangChain, Amazon Bedrock, Amazon Sagemaker, Python, Opensearch, Pgvector, Amazon S3, Amazon Vpc, Aws Iam
**Posted:** 2026-09-08

> Build and operate AWS cloud, ML, LLM, RAG, and IoT infrastructure, including deployment platforms, data pipelines, vector search, observability, security, and cost controls. The role requires deep AWS experience and production experience with LLM-powered applications.

## Job Description

## 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.

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