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Beacon Venture Capital
Beacon Venture Capital
1 – 10 Angajați
FintechInteligență artificială
Beacon Venture Capital este divizia de capital de risc corporativ deținută integral de Kasikornbank PLC, una dintre principalele bănci comerciale din Thailanda. Fondul a fost înființat în 2016 și investește strategic în startupuri din domeniul tehnologiei, de la etapele incipiente până la etapele de creștere, cu un accent principal pe fintech. Printre domeniile sale de interes investițional se numără și afacerile din zona stilului de viață al consumatorilor, precum și domenii de tehnologie avansată, cum ar fi inteligența artificială și tehnologia informației pentru companii. Beacon Venture Capital a fost lansat cu un capital de 30 de milioane de dolari, care a crescut la 135 de milioane de dolari până în 2018.
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Locurile de muncă ale companiei

Senior Cloud Infrastructure Engineer - San Carlos Hybrid

Build secure, scalable AWS infrastructure for LLM, RAG, and machine learning platforms. Support aviation safety technology through cloud operations, data pipelines, and ML platform engineering.

USStatele Unite ale AmericiiCACalifornia
173.000 $ – 225.000 $ / an
HibridNormă întreagăSeniorLimbă Obligatorie: englezăInginer cloud
AirflowAWSCloudDynamoDBPostgresPythonRedisTerraform

Descriere

  • Architect, provision, and maintain AWS environments with infrastructure-as-code tools such as AWS CDK and Terraform.
  • Develop CI/CD workflows and testing for applications, infrastructure, and ML pipelines with GitHub Actions, CodeBuild, and CodePipeline.
  • Run secure cloud networking using VPCs, PrivateLink, and VPC endpoints.
  • Administer IAM, KMS, Secrets Manager, and audit logging controls.
  • Deploy and operate model endpoints with AWS Bedrock and/or SageMaker.
  • Assess ECS, EKS, Lambda, and Batch for inference workloads.
  • Build application services that access LLMs through reliable APIs supporting streaming, batching, and backoff.
  • Develop prompt and tool-execution workflows with LangChain or comparable frameworks, including agents and function calling.
  • Create chunking and embedding pipelines and coordinate them through Step Functions or Airflow.
  • Operate vector search platforms including OpenSearch Serverless, Aurora PostgreSQL with pgvector, and Pinecone.
  • Maintain knowledge bases and synchronize data across S3, Aurora, DynamoDB, and external systems.
  • Develop evaluation harnesses for prompts, retrievers, and chains.
  • Implement application and model observability with CloudWatch and OpenTelemetry.
  • Create token-consumption and cloud-cost dashboards with budgets and alerts.
  • Implement guardrails, rate limiting, fallback handling, and provider routing.
  • Add PII detection and redaction, access controls, content filtering, and human review workflows.
  • Maintain audit trails for regulated operating environments.
  • Develop ingestion and processing workflows for structured, unstructured, and multimedia data.
  • Protect data integrity, lineage, and cataloging with Glue and Lake Formation.
  • Improve bulk data transfer and storage across S3, Glacier, and tiered storage.
  • Use Athena for ad hoc data analysis.
  • Manage infrastructure that deploys to and communicates with edge devices.
  • Support secure messaging, identity management, and over-the-air updates.
  • Work with product and application teams to embed retrieval services, embeddings, and LLM chains in user-facing features.
  • Provide advanced troubleshooting for cloud and machine learning services.
  • Improve retrieval quality, context-window efficiency, and caching with Redis or Bedrock Knowledge Bases.
  • Optimize inference through model selection, quantization, GPU and CPU instance sizing, and autoscaling.

Cerințe

  • At least three years of professional experience, or a relevant master’s degree.
  • Hands-on experience building and managing data pipelines.
  • Experience designing, deploying, and maintaining cloud infrastructure with infrastructure-as-code tools such as AWS CDK.
  • Background building reliable CI/CD and automated testing systems.
  • Experience delivering or operating LLM-powered applications in production.
  • Familiarity with RAG architecture, prompt versioning, and chain orchestration using LangChain or a similar framework.
  • Strong command of AWS services including VPC, IAM, KMS, CloudWatch, S3, ECS/EKS, Lambda, Step Functions, Bedrock, and SageMaker.
  • Experience developing data ingestion and transformation pipelines in Python.
  • Familiarity with Glue, Athena, EventBridge, and SQS.
  • Knowledge of least-privilege access, secrets management, network isolation, and compliance practices.
  • Experience applying quantitative evaluation, A/B testing, and production metrics.
  • Four or more years working with AWS serverless or container platforms is a plus.
  • Experience operating vector databases, OpenSearch, or pgvector at scale is a plus.
  • Familiarity with Bedrock Guardrails, Knowledge Bases, or custom policy engines is a plus.
  • Familiarity with GPU workloads, Triton Inference Server, or TensorRT-LLM is a plus.
  • Experience with big-data technologies for large-scale processing and search is a plus.
  • Experience in aviation data or another safety-critical industry is a plus.
  • DevOps or DevSecOps experience automating CI/CD for ML and application services is a plus.
  • Must be a U.S. Person and authorized to work lawfully in the United States; visa sponsorship and transfers are unavailable.
  • Must work in the United States, be based in or willing to relocate to the San Francisco Bay Area, and work onsite in San Carlos, California at least three days per week.
  • benefits
  • Offers equity.
  • Covers 100% of employee medical premiums.
  • Covers 25% of dependent medical premiums.

Beneficii

  • Offers equity.
  • Covers 100% of employee medical premiums.
  • Covers 25% of dependent medical premiums.
  • Provides three weeks of paid time off.
  • Provides 13 or more paid company holidays.
  • Offers a 401(k) plan.
  • Provides a hybrid schedule with remote work on the remaining days.

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