Senior AI Engineer

🔥 58 minutes ago

🇨🇴 Colombia – Remote

💵 $5k - $6k / month

⏰ Full Time

🟠 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, agentic workflows, multi-step reasoning chains, and orchestrated tool-use pipelines • Translate architectural blueprints into high-performance, production-ready code with error handling, observability hooks, and latency targets • Own end-to-end delivery of AI components from 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 • Apply chunking strategies, embedding models, and re-ranking techniques to improve retrieval accuracy • Implement vector database solutions based on query patterns, data volume, and latency requirements • Diagnose and fix production retrieval failures involving chunking, embedding, indexing, or prompt construction • Build and maintain agentic systems with tool selection, memory architecture, and failure recovery • Manage context-window constraints and graceful degradation • Optimize prompt pipelines for latency and cost using data-driven benchmarks • Deploy AI services with IaC tooling 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 AI'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 • 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 IaC tools such as Terraform or Pulumi • Experience deploying with Docker and Kubernetes • Understanding of maintainable, scalable deployments • Systems design instincts favoring abstraction and reuse • Certified Claude Architect or ability to earn the certification within the first 60 days • AI-native working style using coding assistants effectively • Ability to handle unstructured data problems and legacy integration constraints • Ownership orientation, including early blocker escalation and accountability for system quality

🏖️ Benefits

• Real ownership and end-to-end engagement responsibility • Variety across industries, problems, and client engagements • AI-native culture and use of AI in internal operations • Access to new models and capabilities through partnerships with Anthropic and OpenAI • Early team members share in company success • Small pods and clear accountability • No bureaucracy; best idea wins

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