AI Engineer, English C1

🔥 59 minutes ago

🇨🇴 Colombia – Remote

💵 $3.5k - $4.5k / month

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 AI Engineer

👻 Ghost score 0%

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Cadre AI

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2024

💼 Consulting

🤖 Artificial Intelligence

🤝 B2B

Consulting • Artificial Intelligence • B2B

Cadre AI is an AI strategy and implementation firm that helps companies identify high-impact AI opportunities, integrate AI into existing tech stacks, and deliver measurable business results such as revenue growth and improved EBITDA. They offer services across AI Strategy, AI Leadership & Facilitation (training/executive enablement), AI Engineering, and AI Agents (autonomous workflows), plus tools like an AI Maturity Index and a centralized results portal. Cadre AI works across industries including professional services, private equity, real estate, financial services, mortgage & lending, construction, retail & e-commerce, and manufacturing & logistics, and focuses on enabling business teams (sales, marketing, customer success, finance, operations, technology, legal, executive leadership) to adopt and scale AI effectively. They position themselves as a practical, conservative partner that prefers activating existing tool capabilities when possible and building custom solutions only when necessary.

📋 Description

• Design and build complex backend AI modules, custom agentic workflows, multi-step reasoning chains, and orchestrated tool-use pipelines • Translate AI strategists' architectural blueprints into high-performance, production-ready code • Own end-to-end delivery of AI components from initial scaffold through deployment • Use AI coding assistants to accelerate output while maintaining code quality and architectural integrity • Architect and optimize RAG pipelines over unstructured, messy, and multi-modal data • Implement vector database solutions based on query patterns, data volume, and latency requirements • Diagnose and fix production retrieval failures involving chunking, embeddings, indexing, or prompt construction • Build and maintain agentic systems with deliberate tool selection, memory architecture, and failure recovery • Manage context-window constraints and prevent silent loss of critical information • Optimize prompt pipelines for latency and cost using benchmarking • Deploy AI services with Infrastructure as Code and containerized environments • Write unit, integration, and AI evaluation tests • Maintain production systems with structured logging, alerting, and cost monitoring • Abstract reusable internal tools, libraries, and services from client engagement patterns • Document internal tools for independent use by other engineers • Contribute to Cadre's internal AI platform, architecture reviews, and improvement proposals

🎯 Requirements

• 3+ years of backend engineering experience • At least 1 year building and shipping production AI agents in a client-facing or fast-paced product environment • Deep hands-on experience with vector databases, advanced RAG optimization, and agentic orchestration • Proficiency in Python and Node.js • Strong command of backend architecture patterns, including API design, async processing, parallel execution, and secure credential handling • Experience with Infrastructure as Code tools such as Terraform or Pulumi • Experience deploying with Docker and Kubernetes • Understanding of maintainable infrastructure at scale • Systems design skills favoring abstraction and reuse • Certified Claude Architect or demonstrated ability to earn the certification within the first 60 days • Experience using AI coding assistants effectively • Ability to handle unstructured data problems and legacy integration constraints • Ownership orientation, including finishing work, flagging blockers early, and maintaining high-quality systems

🏖️ Benefits

• Early team members share in the success they help create • Access to new models and capabilities through partnerships with Anthropic, OpenAI, and YC • AI-native culture and use of AI in internal operations • End-to-end ownership and clear accountability • Small pods and low-bureaucracy environment

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