Job Closed
This listing is no longer active.
AI Architect
Location
Florida
Posted
120 days ago
Salary
0
Seniority
Senior
Job Description
AI Architect
qode.world
• Define and own end-to-end AI architecture for multiple enterprise use cases, including data flows, model lifecycle, and serving patterns across Azure and AWS. • Design AI/ML solution blueprints covering data ingestion, feature stores, training pipelines, model registry, deployment, monitoring, retraining, and decommissioning. • Establish and standardize MLOps frameworks (MLflow/Kubeflow/Airflow, Docker, Kubernetes) and reference implementations that AI/ML engineers and data scientists can reuse across teams. • Collaborate with product, data, and business stakeholders to identify AI opportunities, shape solution options, and align AI architectures with business and non-functional requirements (scalability, reliability, cost, latency). • Define and enforce governance for model approval, explainability, versioning, drift monitoring, and compliance with data privacy and regulatory requirements relevant to the organization. • Guide the selection and integration of cloud-native services (Azure ML, AWS SageMaker, Lambda, EC2, S3, Azure Functions, API gateways, monitoring stacks) into cohesive AI platforms. • Work closely with security, compliance, data, and enterprise architecture teams to ensure AI solutions meet standards for security, resilience, observability, and cost optimisation. • Provide technical leadership and mentoring to AI engineers, ML engineers, and data scientists on best practices in AI architecture, MLOps, and cloud-native design. • Create and maintain architectural artefacts: high-level designs, detailed solution diagrams, standards, and documentation for AI platforms and reference solutions.
Job Requirements
- Proven experience designing and leading AI/ML solution architectures in production across multiple projects or products.
- Ability to translate business use cases into architectural blueprints, roadmaps, and reusable platform components.
- Strong understanding of ML techniques (supervised, unsupervised, basic deep learning) and their productionisation for real-world use cases.
- Hands-on experience defining MLOps strategies using MLflow, Kubeflow, Airflow, Docker, and Kubernetes for large-scale deployments.
- Expert knowledge of Azure ML and AWS SageMaker, plus core services (S3, EC2, Lambda, Azure Functions, identity, networking, monitoring).
- Experience designing multi-environment (dev/test/prod) AI platforms with robust CI/CD, model promotion, and rollback strategies.
- Understanding of data privacy, security, and responsible AI principles (fairness, transparency, explainability, auditability).
- Experience defining policies and controls for model governance and risk management.
- Strong Python skills and familiarity with common ML libraries (Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch).
- Solid grounding in CI/CD (GitHub Actions, Azure DevOps, AWS CodePipeline) and monitoring/logging solutions (Prometheus, Grafana, or cloud-native equivalents).
- 7–10 years overall experience (minimum 5+ years in AI/ML, with strong MLOps and cloud experience).
Benefits
- Competitive compensation and benefits packages
- Health insurance
- Paid time off
- Professional development opportunities
Related Guides
Related Job Pages
More AI Engineer Jobs
• Define the technical vision and architecture for AI-orchestrated developer workflows at Canva • Establish new engineering paradigms around AI tooling, agent orchestration, and context engineering • Architect foundational AI systems and frameworks that become the platform every engineer at Canva relies on • Drive industry-leading practices in agentic AI development and enterprise-scale AI tooling adoption • Shape and mentor engineers joining the expanded team through technical leadership and vision-setting • Solve challenges no one's solved before with access to state-of-the-art tooling, models, and infrastructure • Define and architect our enterprise-level strategic vision and technical roadmap for AI-orchestrated developer workflows at Canva • Pioneer new AI engineering practices by researching and developing high-value AI methodologies, frameworks, and technologies that go beyond code generation to transform all parts of the Canva SDLC • Drive paradigm shift in how engineering teams think about and adopt AI tooling, establishing patterns and practices that influence the broader industry • Keep Canva at the bleeding edge through deep industry research, experimentation with emerging AI technologies, and strategic evaluation of new paradigms (MCPs, Skills, multi-agent frameworks)
Junior AI Engineer
Metova, Inc.Helping companies transform their business through technology to meet the growing expectations of their customers.
• Experiencia depslegando y programando soluciones basadas en agentes inteligentes y LLMs, integrando herramientas como LangChain, LlamaIndex, AutoGen, CrewAI o frameworks equivalentes. • Implementar agentes que interactúan con usuarios, APIs, sistemas ERP o plataformas externas (e.g. WhatsApp, sistemas contables, CRMs). • Implementar arquitecturas MCP (Model Context Protocol) y A2A (Agent-to-Agent) para permitir coordinación multi-agente y flujos autónomos dentro de entornos empresariales. • Trabajar en ambientes productivos y con interacción directa con equipos de infraestructura, DevOps y MLOps • Colaborar estrechamente con equipos de producto, UX, datos y backend para tener un delivery exitoso de las funcionalidades planeadas. • Implementar con buenas prácticas de desarrollo, validación y monitoreo de agentes, incluyendo tests de integración, control de versiones de prompts y trazabilidad de decisiones. • Mantenerse actualizado en frameworks de código abierto y papers relevantes en el campo de agent frameworks, memory architectures y multi-agent systems.
• Design, build, and maintain scalable, fault-tolerant AI systems leveraging OpenAI and Anthropic models. • Develop RAG architectures to ensure efficient, high-performance information retrieval tailored to chemical and materials science. • Optimize system performance to handle large-scale data and application demands. • Build and maintain intelligent AI agents using modern frameworks. • Collaborate with domain experts to refine agent capabilities for specific scientific workflows. • Architect and maintain vector database solutions for efficient data storage and retrieval. • Develop pipelines for ingestion, transformation, and storage to enable AI/ML workflows. • Implement robust error-handling, monitoring, and alerting mechanisms to ensure system resilience. • Troubleshoot and resolve system bottlenecks and failures. • Design, implement, and maintain CI/CD pipelines for AI systems and data workflows. • Stay informed on the latest trends and tools in AI/ML engineering and agent technologies. • Work closely with AI/ML, data engineering, and platform teams to understand and deliver on technical requirements.
Senior AI Engineer – AI Lead, LLMs, Prompt Engineering, AI Systems
Persian HorizonWith over 28 years of experience in Business Setup, Investment
• Design and implement end-to-end AI and LLM-based systems • Work extensively with Large Language Models (LLMs) • Build and maintain advanced Prompt Engineering frameworks • Design and manage Knowledge Bases for AI (company content, documents, data) • Fine-tune and train AI models using internal organizational data • Implement RAG architectures using Vector Databases • Integrate and orchestrate multiple AI APIs (OpenAI, Anthropic, Gemini, Azure AI, etc.) • Convert AI outputs into usable tools for sales, marketing, content, and analytics teams • Design AI infrastructure ready for SaaS and client-facing products • Collaborate closely with Full Stack Developers and business stakeholders
