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Beacon Venture Capital
Beacon Venture Capital
1 – 10 कर्मचारी
कृत्रिम बुद्धिमत्ताफिनटेक
Beacon Venture Capital, थाईलैंड के एक प्रमुख वाणिज्यिक बैंक Kasikornbank PLC की पूर्ण स्वामित्व वाली कॉर्पोरेट वेंचर कैपिटल शाखा है। वर्ष 2016 में स्थापित यह फंड शुरुआती चरण से लेकर विकास चरण तक प्रौद्योगिकी स्टार्टअप्स में रणनीतिक निवेश करता है और इसका मुख्य ध्यान फिनटेक पर है। इसके निवेश हितों में उपभोक्ता जीवनशैली से जुड़े व्यवसाय और कृत्रिम बुद्धिमत्ता तथा एंटरप्राइज़ आईटी जैसे डीप टेक्नोलॉजी क्षेत्र भी शामिल हैं। Beacon Venture Capital ने 30 मिलियन डॉलर की पूंजी के साथ शुरुआत की और 2018 तक यह बढ़कर 135 मिलियन डॉलर हो गई।
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कंपनी की नौकरियाँ

Staff Software Engineer, Artificial Intelligence and LLM

Lead development of LLM-powered aviation capabilities for Beacon AI’s safer-flight platform, covering RAG, tool calling, evaluation, safety, and production reliability.

USसंयुक्त राज्यCAकैलिफ़ोर्निया
$2,24,000 – $2,60,000 / वर्ष
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AWSDynamoDBPythonTypeScript

विवरण

  • Build user-facing LLM product capabilities from design through production
  • Architect retrieval-augmented generation and tool-calling workflows
  • Produce reliable JSON and schema-constrained outputs with validation, retries, and fallback handling
  • Use function calling to connect internal tools, search, routing, and data services
  • Develop Python or TypeScript APIs and workers with explicit contracts, streaming, and backoff
  • Use caching, request shaping, prompt templates, and context packing to manage latency and cost
  • Connect applications to AWS Bedrock, OpenAI, Anthropic, or self-hosted model endpoints
  • Work with infrastructure engineers on chunking, embeddings, and indexing for documents, time series, and multimedia
  • Select and optimize vector databases including OpenSearch, pgvector, and Pinecone
  • Keep knowledge bases current by synchronizing data from S3, Aurora, DynamoDB, and external sources
  • Build offline evaluations and golden datasets for prompts, retrievers, and tools
  • Define online measures for task success, hallucination rate, retrieval precision and recall, p95 latency, and per-request cost
  • Conduct A/B tests and roll out prompt and version changes with guardrails and canary releases
  • Implement content and policy enforcement, PII detection and redaction, access controls, and audit trails
  • Create human-in-the-loop workflows for sensitive operations
  • Process aviation data in line with internal security standards
  • Provide tracing, logging, and dashboards for model calls, token usage, errors, and system saturation
  • Investigate failures across retrieval, prompts, tools, and model providers
  • Set technical direction across services and teams for complex, ambiguous problems
  • Work with ML, infrastructure, and product partners on user experience, outcomes, reliability, and safety-critical systems

आवश्यकताएँ

  • At least 8 years of experience, including ownership of systems or standards used by other engineers
  • Alternatively, a related master’s degree plus 4 years of relevant experience
  • Experience launching LLM features for end users and improving them through data
  • Strong production development, testing, and technical documentation skills
  • Knowledge of embeddings, chunking, vector-search tradeoffs, and function calling
  • Experience designing evaluations, establishing success metrics, and iterating from evidence
  • Ability to monitor p95 latency, satisfy SLAs, and lower costs while preserving quality
  • Ability to communicate tradeoffs and align product, infrastructure, and security stakeholders
  • Technical leadership experience setting direction or standards adopted by engineers or teams
  • Proficiency in Python or TypeScript
  • Experience with RAG, tool-calling workflows, schema-constrained JSON, validation, retries, fallbacks, APIs, workers, streaming, backoff, caching, prompt templates, context packing, and model providers
  • Experience using AWS Bedrock, OpenAI, Anthropic, or self-hosted endpoints
  • Familiarity with OpenSearch, pgvector, Pinecone, or Weaviate
  • Experience working with S3, Aurora, and DynamoDB data sources
  • Experience with offline evaluation, golden datasets, online metrics, A/B testing, prompt and version rollouts, guardrails, and canary releases
  • Experience implementing content and policy controls, PII detection and redaction, access management, and auditing
  • Experience with tracing, logging, dashboards, model-call troubleshooting, and production operations
  • U.S. Person status is required; visa sponsorship and transfers are not available
  • All work must be performed within the United States
  • Ability to work in the San Francisco Bay Area or San Carlos, California, at least 3 days per week onsite

लाभ

  • Equity is offered
  • 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 offered
  • Remote work is available on the remaining hybrid-schedule days

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