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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

Staff Software Engineer, Cloud Infrastructure (San Carlos Hybrid)

Lead secure AWS cloud infrastructure and LLM platform development for Beacon AI’s aviation systems. Build RAG, machine learning infrastructure, data pipelines, and production cloud operations.

USStatele Unite ale AmericiiCACalifornia
224.000 $ – 260.000 $ / an
HibridNormă întreagăLiderLimbă Obligatorie: englezăInginer cloud
AWSCloudDynamoDBPostgresPython

Descriere

  • Lead development of Beacon AI’s AWS foundation and LLM platform
  • Design, provision, maintain, and operate secure, reliable, scalable AWS infrastructure
  • Develop CI/CD pipelines and testing for applications, infrastructure, and machine learning workflows
  • Administer secure networking, IAM, KMS, Secrets Manager, and audit logging
  • Operate model endpoints through AWS Bedrock and SageMaker
  • Develop application services that access LLMs through APIs with streaming, batching, and backoff
  • Implement prompt and tool execution workflows with LangChain or comparable frameworks
  • Design chunking, embedding, ingestion, and processing pipelines for structured, unstructured, time-series, and multimedia data
  • Operate vector search with OpenSearch Serverless, Aurora PostgreSQL with pgvector, or Pinecone
  • Build and maintain knowledge bases and synchronize data from S3, Aurora, DynamoDB, and external sources
  • Create evaluation systems that measure quality, latency, regressions, telemetry, token consumption, and costs
  • Implement guardrails, rate limiting, fallbacks, provider routing, PII detection, redaction, access controls, content filtering, and audit trails
  • Develop data pipelines with Glue, Lake Formation, S3, Glacier, Athena, and related AWS services
  • Manage infrastructure that connects with edge devices through secure messaging, identity, and over-the-air updates
  • Collaborate with product and application teams to incorporate retrieval services, embeddings, and LLM chains into user-facing capabilities
  • Provide advanced troubleshooting for cloud and machine learning services
  • Improve retrieval quality, context-window efficiency, caching, inference, model selection, hardware choices, and autoscaling
  • Own delivery from system design through production operations, including on-call support and ongoing improvement

Cerințe

  • Bring at least 8 years of professional experience, or a relevant master’s degree with 5 years of related experience
  • Have experience building and operating data pipelines
  • Have designed, deployed, and maintained cloud infrastructure with Infrastructure as Code tools such as AWS CDK
  • Have built dependable CI/CD and testing systems
  • Have shipped or operated LLM-powered applications in production
  • Understand RAG architecture, prompt versioning, and chain orchestration with LangChain or a similar framework
  • Demonstrate strong knowledge of AWS services including VPC, IAM, KMS, CloudWatch, S3, ECS/EKS, Lambda, Step Functions, Bedrock, and SageMaker
  • Have built ingestion and transformation pipelines in Python
  • Be familiar with Glue, Athena, EventBridge, and SQS
  • Understand least-privilege access, secrets management, network isolation, and compliance practices
  • Have applied quantitative evaluation, A/B testing, and live operational metrics
  • Be a U.S. Person
  • Be legally authorized to work in the United States
  • Be able to work without employment visa sponsorship or visa transfer
  • Be willing to work in or relocate to the San Francisco Bay Area
  • Be able to work onsite in San Carlos, California at least three days per week

Beneficii

  • The company covers 100% of employee medical premiums and 25% of dependent premiums
  • Three weeks of paid time off
  • At least 13 paid company holidays
  • 401(k) plan offered
  • Equity offered
  • Remote work available on the remaining days of the hybrid schedule

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