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Beacon Venture Capital
Beacon Venture Capital
1 – 10 Employees
Artificial IntelligenceFintech
Beacon Venture Capital is the wholly owned corporate venture capital arm of Kasikornbank PLC, a leading commercial bank in Thailand. Established in 2016, the fund invests strategically in technology startups from early through growth stages, with a primary focus on fintech. Its investment interests also include consumer lifestyle businesses and deep technology areas such as artificial intelligence and enterprise IT. Beacon Venture Capital launched with $30 million in capital and grew to $135 million by 2018.
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Senior Software Engineer, Artificial Intelligence and LLM

Build and operate production LLM capabilities for Beacon AI’s aviation safety platform. Lead retrieval, tool calling, evaluation, and reliable service delivery.

USUnited StatesCACalifornia
$173,000 – $225,000 / year
HybridFull-timeSeniorEnglish RequiredAI EngineerMachine Learning Engineer
AWSDynamoDBPythonTypeScript

Description

  • Build retrieval-augmented generation and tool-calling workflows
  • Produce validated JSON and schema-constrained outputs with retries and fallback handling
  • Connect function calling to internal tools, search, routing, and data services
  • Develop Python or TypeScript APIs and workers with defined contracts, streaming, and backoff
  • Use caching, request shaping, prompt templates, and context packing to manage latency and costs
  • Integrate foundation model services from AWS Bedrock, OpenAI, Anthropic, and self-hosted endpoints
  • Help develop chunking, embedding, and indexing strategies for documents, time series, and multimedia
  • Select and optimize vector databases including OpenSearch, pgvector, and Pinecone
  • Keep knowledge bases synchronized with S3, Aurora, DynamoDB, and external data sources
  • Develop offline evaluations and golden datasets for prompts, retrievers, and tools
  • Define production metrics covering task success, hallucination rate, retrieval precision and recall, p95 latency, and cost per request
  • Conduct A/B tests and manage guarded prompt and version releases with canary deployments
  • Implement content and policy safeguards, PII detection and redaction, access controls, and audit trails
  • Create human-review workflows for sensitive actions
  • Instrument model calls with tracing, logging, and dashboards for token usage, errors, and saturation
  • Investigate issues across retrieval systems, prompts, tools, and model providers
  • Work with product, infrastructure, ML, and security teams to deliver dependable aviation systems
  • Create user-facing LLM capabilities for Beacon AI’s platform to make flying safer, more efficient, and more capable

Requirements

  • 5–8 years of experience, including experience delivering production ML or LLM systems
  • Demonstrated experience launching LLM features for users and improving them through data
  • Strong production software development, testing, and documentation skills
  • Working knowledge of embeddings, chunking, vector search tradeoffs, and function calling
  • Experience creating evaluations, defining success measures, and iterating from evidence
  • Ability to monitor p95 latency, meet SLAs, and lower costs while maintaining quality
  • Ability to take ownership of features from design through production with limited supervision
  • Experience with Bedrock, OpenSearch Serverless, pgvector, Pinecone, or Weaviate is preferred
  • Experience with prompt versioning, guardrails, and model-provider routing is preferred
  • Experience with multimodal data such as time series or video is preferred
  • Familiarity with GPU inference, Triton, or TensorRT-LLM is preferred
  • Exposure to aviation or another safety-critical industry is preferred
  • Working knowledge of CI/CD, infrastructure as code, and secure secrets management is preferred
  • Must qualify as a U.S. Person
  • Must be legally authorized to work in the United States
  • Visa sponsorship and visa transfers are not available
  • All work must be performed within the United States
  • Must live in or be willing to relocate to the San Francisco Bay Area
  • Must work onsite in San Carlos, California, at least three days per week
  • Must be available for full-time work

Benefits

  • Equity is included in the offer
  • The company covers 100% of employee medical premiums
  • The company covers 25% of dependent medical premiums
  • Three weeks of paid time off
  • At least 13 paid company holidays
  • 401(k) plan available
  • Flexible remote work on the remaining days of the hybrid schedule

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