AI Engineer

Provável vaga fantasma

🕒 Janeiro 12

🇮🇳 Índia – Remoto

⏰ Tempo Integral

🟡 Pleno

🟠 Sênior

🤖 Engenheiro de IA

🗣️🇺🇸🇬🇧 Inglês obrigatório

De onde vem esta vaga

Publicada na página de carreiras da Opplane ↗página de carreiras da Opplane, não em um site de vagas

Vista pela primeira vez pelo Remote Rocketship Janeiro 12

Ainda aberta no site da Opplane. Verificada 8 horas atrás.

Candidatar-se
Logo of Opplane

Opplane

11 - 50 funcionários

Fundada em 2018

🤖 Inteligência Artificial

💳 Fintech

☁️ SaaS

🔥 Investimento no último ano

💰 Accelerator/Incubator em 2025-12

Artificial Intelligence • Fintech • SaaS

A Opplane é uma empresa de software que ajuda organizações a aproveitar o valor dos dados por meio de conectividade, governança de dados e inteligência artificial generativa. A empresa se concentra na aplicação de soluções de dados orientadas por IA em ambientes regulados, especialmente nos setores bancário e de fintech, viabilizando conformidade, conectividade segura de dados e casos de uso de IA para serviços financeiros e empresas.

Descrição

• Build and orchestrate LLM agents using Gemini Pro and LangChain • Design, implement, and operate RAG solutions at scale • Integrate with Gemini and Vertex AI services using API-driven architectures • Debug and optimize end-to-end LLM pipelines, including: chunking strategies, embeddings, retrieval logic, LLM response behavior • Deliver production-ready AI services, including monitoring, rate limiting, and reliability controls • Participate in solution design and technical decision-making • Continuously evaluate and experiment with new LLM models and features as they become available • Implement AI safety, security, and compliance controls across the AI lifecycle • Collaborate with cross-functional teams across time zones

🎯 Requisitos

• Strong AI Engineer / Senior Individual Contributor • Hands-on experience integrating Gemini Pro 1.x via API endpoints • Strong experience building LLM agents using LangChain or similar frameworks • Advanced understanding of prompt engineering and agent orchestration • Proven ability to debug end-to-end LLM systems, including chunking, embeddings, retrieval, and generation layers • Hands-on experience with vector databases (Pinecone, Chroma, FAISS) • Strong understanding of RAG architectures at scale • Practical knowledge of RAG evaluation metrics, including: Precision@K, Recall@K, MRR, nDCG, Faithfulness and Answer Relevance • Strong hands-on experience with Google Cloud Platform, including: Storage services, Serverless compute, Search, Transcription, Chat / conversational services • Practical experience in multi-cloud environments • Working experience integrating AWS services alongside GCP • Excellent programming skills in Python, PySpark, or Java • Strong experience building scalable, API-based AI solutions • Solid understanding of API rate limiting, performance tuning, and reliability • Hands-on experience implementing AI safety and guardrails, including: Input validation, PII detection and redaction, Reliability and hallucination checks, Compliance controls • Knowledge of multi-layered security, including IAM, data isolation, and audit logging

🏖️ Benefícios

• Competitive salary • Flexible working hours • Professional development budget • Home office setup allowance • Global team events

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Desenvolvido por Lior Neu-ner. Adoraria receber seu feedback — entre em contato por DM ou pelo e-mail support@remoterocketship.com
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