Blue Polaris is a forward-thinking technology company specializing in intelligent automation, AI-powered business solutions, and large-scale digital transformation for global clients. The company delivers cutting-edge systems that combine machine learning, process automation, and data intelligence to create measurable business impact across industries. About the Role We are seeking an AI Architect to design, lead, and govern the end-to-end architecture of AI and ML systems across our LATAM engagements. This is a deep technical leadership role — you will own the architectural vision, define standards, evaluate emerging technologies, and ensure that AI solutions are scalable, secure, and production-ready. You will serve as the technical authority who bridges business strategy and engineering execution. This position is open to both contractors and full-time employees. Candidates must be open to either engagement model, as the arrangement may evolve based on project needs and business requirements. Key Responsibilities Design end-to-end AI/ML solution architectures: data ingestion, feature engineering, model training, serving, and monitoring layers Define architectural standards for LLM-based systems including RAG pipelines, agent frameworks, fine-tuning strategies, and prompt governance Lead solution design sessions with clients and internal stakeholders, translating requirements into scalable technical blueprints Evaluate and select AI/ML platforms, cloud services, and open-source frameworks aligned with business and security requirements Establish MLOps maturity: CI/CD for models, drift detection, retraining pipelines, model versioning, and observability Conduct architecture reviews and technical audits on existing AI systems; identify risks and recommend improvements Collaborate with data engineers, ML engineers, and DevOps teams to ensure architectural intent is implemented correctly Contribute to building the AI Center of Excellence within the LATAM practice Support pre-sales and proposal efforts with technical architecture diagrams, effort estimates, and risk assessments Stay current with GenAI, foundation models, multi-modal systems, and emerging architecture patterns Required Qualifications Education & Experience Bachelor's or Master's in CS, AI, ML, or related field 6–15 years of experience in AI/ML engineering Experience in architecture or principal-level technical roles Proven delivery of production AI systems at scale Core Technical Skills PyTorch and/or TensorFlow Cloud architecture: AWS, Azure, or GCP MLOps tools: MLflow, Kubeflow, SageMaker, Vertex AI AI/ML Technical Depth LLM integration, RAG, and agent frameworks Neural network design and training at scale Microservices and API design for AI systems Data architecture and feature store design Security and compliance in ML systems Solution documentation and diagramming Preferred Qualifications Experience with multi-agent systems and orchestration frameworks (LangChain, LangGraph, AutoGen, CrewAI) Familiarity with enterprise AI governance, responsible AI practices, and model risk frameworks Exposure to real-time inference, edge AI, or embedded ML deployments Cloud certifications: AWS Solutions Architect, Google Professional ML Engineer, or Azure AI Engineer Spanish or Portuguese fluency preferred for LATAM client engagement Prior consulting or professional services background #J-18808-Ljbffr