Bolder Apps
Bolder Apps
Bolder Apps — bosh qarorgohi Mayamida joylashgan, butun dunyodagi startaplar va bizneslar bilan hamkorlik qiluvchi, sun’iy intellektga yo‘naltirilgan mobil va veb-ilovalar ishlab chiqish agentligidir. Uning jamoasi strategiya va UI/UX dizaynidan tortib Flutter, Swift va Kotlin yordamida mahalliy hamda kross-platformali mobil dasturlashgacha, shuningdek React, Node.js va Laravel asosidagi veb-ishlab chiqishgacha mahsulot hayotiy siklining barcha bosqichlarini qo‘llab-quvvatlaydi. Agentlik backend arxitekturasi, o‘sishni optimallashtirish, mutaxassislar bilan jamoani kuchaytirish, doimiy qo‘llab-quvvatlash va sun’iy intellekt integratsiyalarini ham taklif etadi. Bolder Apps fintech, sog‘liqni saqlash, elektron tijorat, ijtimoiy media va turmush tarzi loyihalarida ishlaydi. Shu sababli u mahsulot muhandisligi, mijozlarga xizmat ko‘rsatish va amaliy sun’iy intellektni ishlab chiqishga qiziqadigan nomzodlar uchun mos keladi.

LLM Application Engineer - Argentina Remote

Build and operate production-grade LLM pipelines for Bolder Apps, an AI product studio. Lead extraction, evaluation, reliability, and cost optimization across multimodal workflows.

Tavsif

  • Lead end-to-end production LLM pipelines spanning ingestion, multimodal model calls, structured records, storage, confidence scoring, retries, and idempotent rescans.
  • Develop prompt and schema strategies, including constrained or schema-aligned outputs, to produce consistent, product-ready results.
  • Create classification and filtering systems with taxonomy mapping, demographic or audience criteria, deduplication, and data cleanup.
  • Build evaluation harnesses using golden datasets, regression testing, and live production metrics.
  • Track quality against targets for completeness, duplicate rates, incorrect inclusions, image availability, and related product SLAs.
  • Reduce latency and spending through token controls, model tier selection, caching, and batching.
  • Strengthen long-running asynchronous jobs with timeouts, partial recovery, memory controls, and safe production releases.
  • Work with Flutter/mobile and QA teams on field contracts, review workflows, and incident investigation.
  • Maintain architecture documentation and operational runbooks that support shared ownership.
  • Monitor Gemini and comparable LLM APIs, recommending model changes, fallback strategies, and schema refinements.

Talablar

  • Demonstrated experience delivering production LLM applications, including prompting, structured outputs, retries, observability, and failure recovery.
  • Advanced hands-on experience with Google Gemini for multimodal text, image, and document workflows and structured extraction.
  • Practical experience with at least one additional major LLM platform, such as OpenAI or Anthropic.
  • Experience extracting structured information from HTML, PDFs, images, and mixed email-style content.
  • Experience developing classification and taxonomy systems driven by LLM outputs.
  • Strong evaluation practice covering offline tests, regression suites, and production metrics tied to defined acceptance criteria.
  • Understanding of cost and latency controls, including token budgets, lower-cost model tiers, caching, and batching.
  • Python backend experience with serverless cloud platforms such as Cloud Functions and document databases such as Firestore, or comparable GCP patterns.
  • English proficiency at C1 level or higher.
  • Availability for working-hours overlap through approximately 5 PM EST when live coordination is required.
  • A strong ownership mindset, including realistic estimates, early escalation of blockers, and completed releases.
  • Preferred experience includes schema-aligned LLM frameworks, Google Document AI or comparable OCR/document intelligence, Gmail API/OAuth compliance, computer vision, Firebase/GCP operations, production evaluation datasets, or agency and multi-client studio work.

Imtiyozlar

  • Fully remote, async-friendly work with overlap through approximately 5 PM EST when client or release coordination requires it.
  • Monthly retainer engagement focused on recurring AI pipeline work and maintaining production quality and cost control.
  • Substantial autonomy over prompt design, schemas, evaluation methods, and deployment practices.
  • Direct collaboration with project managers, mobile engineers, and decision-makers.
  • Budget for the LLM and cloud tools needed to deliver effectively.
  • Access to a peer network of product-focused builders working across related client projects.

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