
51 - 200 funcionários
Ottimate é uma empresa de tecnologia especializada na automação de contas a pagar (AP). Com suas soluções orientadas por IA, a Ottimate racionaliza todo o processo de AP, desde a codificação e roteamento de faturas até os pagamentos, ajudando as empresas a economizar tempo e reduzir erros. Ela se integra perfeitamente a vários sistemas contábeis, fornecendo visibilidade em tempo real dos gastos e conformidade com as políticas financeiras. A plataforma foi projetada para melhorar a eficiência dos profissionais de finanças, permitindo que as organizações se concentrem na tomada de decisões estratégicas e na otimização de suas operações comerciais.
🕒 Julho 31
🇺🇸 Estados Unidos – Remoto (EUA)
💵 $200.000 - $225.000 / ano
⏰ Tempo Integral
🔴 Especialista
🤖 Engenheiro de IA
👻 Score fantasma 0%
🗣️🇺🇸🇬🇧 Inglês obrigatório
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51 - 200 funcionários
Ottimate é uma empresa de tecnologia especializada na automação de contas a pagar (AP). Com suas soluções orientadas por IA, a Ottimate racionaliza todo o processo de AP, desde a codificação e roteamento de faturas até os pagamentos, ajudando as empresas a economizar tempo e reduzir erros. Ela se integra perfeitamente a vários sistemas contábeis, fornecendo visibilidade em tempo real dos gastos e conformidade com as políticas financeiras. A plataforma foi projetada para melhorar a eficiência dos profissionais de finanças, permitindo que as organizações se concentrem na tomada de decisões estratégicas e na otimização de suas operações comerciais.
• Architect and ship production AI/ML systems — you write code, not just review it • Own the AI roadmap end-to-end: prioritization, trade-offs, delivery • Set technical standards for model quality, evals, observability, and reliability • Drive adoption of agentic coding tools to multiply team velocity • Claude Code, Cursor, Copilot, or equivalent — measure and improve PR throughput • Partner with Platform Engineering on infrastructure, data pipelines, and APIs • Manage a distributed team of 8–10 engineers across Data and ML disciplines • Hire, develop, and retain engineers at all levels; build a high-trust remote culture • Partner with Product on roadmap sequencing and scope trade-offs • Work directly with customer-facing teams to close feedback loops on model quality • Communicate AI capabilities and limitations clearly to non-technical stakeholders • Own model performance metrics and drive continuous improvement pipelines • Build and maintain evals frameworks — regression suites, human review, A/B testing • Oversee training data collection, curation, and labeling operations • Manage the full ML lifecycle: experimentation, deployment, monitoring, iteration • Define and enforce quality bars for agentic workflows entering production
• Production agentic pipelines using frontier models • Anthropic SDK · OpenAI SDK · tool use, function calling, multi-agent orchestration • Reliable agent loop design — planning, memory, tool execution, error recovery • RAG pipeline design — chunking, embedding models, retrieval tuning, reranking • Evals frameworks built from scratch — correctness, regression, semantic similarity • Observability for production AI — tracing, cost tracking, latency, failure analysis • Fine-tuning frontier or open-source models for domain-specific tasks • LoRA, QLoRA, instruction tuning — not just off-the-shelf API calls • Training data collection, curation, cleaning, and labeling at scale • LLM inference and serving optimization • vLLM, TGI, or equivalent • Model selection trade-offs — cost, latency, capability, context window • Hands-on Python — comfortable writing, reviewing, and shipping production code • PostgreSQL — schema design, query optimization, indexing strategies • Distributed systems — async workers, queues, retries, state machines • Celery or similar async task frameworks is a bonus • Public-facing API design — REST, versioning, developer experience • MCP server development — tool-accessible APIs for AI agent integration • AWS or cloud infrastructure — enough to own AI workload deployments • Engineering Manager ready for director-level ownership • Has led technical teams at a startup or growth-stage company — knows how to move fast • Hands-on contributor who has also managed small high performance teams. • Comfortable owning outcomes • Exceptional AI engineering skills are the primary bar. We will teach the domain.
• Compensation: 200,000-225,000 + 15% Annual Bonus + Equity • Competitive salary based on skills & experience. • Medical, Dental, Vision and other Company-Subsidized Benefits for you and your family. • Employer sponsored 401(k) with company match. • Paid Time Off (and the encouragement to use it). • Annual company retreats. • Promote from within philosophy. • You will be part of a growing team, at a pinnacle moment of scale for the business, and experience the excitement of working in a startup where each action makes a huge difference. • You will have the agency to solve difficult problems creatively, the freedom to explore work that inspires you, and infrastructure to ensure you're constantly challenged and developing. • You will work with sharp, passionate teammates solving some of the most unique challenges and positioning our product as a premier finance automation solution. • Our commitment to empowering a diverse and inclusive workforce, celebrating differences, and creating a safe space for our employees to bring their whole selves to work is second to note. • We are transforming entire industries using innovative technology including Artificial Intelligence, Payment Tech, and Neural Networks. • Our leaders lead with a people-first approach; inspiring excellence, nurturing ideas, and finding creative ways to eliminate obstacles for cultivating growth. • We truly love what we do and who we do it with - and we think you will too!
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