Senior AI Architect

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Overview

LABUR is partnering with a client to identify a Sr. AI Architect who will lead the design and delivery of enterprise-scale AI solutions, including LLM-powered assistants, RAG workflows, and agent-based systems. This individual will play a central role in shaping system design, governance, and best practices across the AI portfolio while balancing speed, quality, and scalability.

Responsibilities

• Lead design and delivery of enterprise AI solutions, including LLM assistants, RAG workflows, and agent-based systems, balancing speed, quality, and scalability.
• Define and enforce reference architectures, reusable components, and internal best-practice artifacts for AI projects to ensure consistency and maintainability.
• Provide architectural reviews and guidance to project teams, ensuring alignment with enterprise standards, security, compliance, and validation requirements.
• Develop LLM-powered assistants and copilots that execute real-world workflows such as customer support automation, knowledge summarization, and enterprise search using Agentic AI frameworks (LangChain Agents, Bedrock Agents).
• Build, maintain, and optimize semantic search and vector pipelines, including ingestion, embeddings, and indexing, for performance and relevance.
• Establish and drive LLMOps approaches covering prompt and model versioning, agent lifecycle management, feedback loops, and continuous evaluation.
• Mentor engineering teams on generative AI techniques, fine-tuning, prompt engineering, ethics, and explainability.
• Ensure AI solutions adhere to regulatory and validation standards (e.g., FDA validation for AI software used in manufacturing), internal governance, and secure operations.
• Rapidly prototype new AI methods and components, including multimodal and agentic workflows, to validate feasibility and incorporate into enterprise systems.
  
  

Qualifications

• 10 years of overall professional experience, including 7 years in software engineering and AI/ML with 3 years specializing in Generative AI and LLMs.
• Proven track record designing, deploying, and scaling enterprise AI/LLM solutions across real-world use cases.
• Strong hands-on expertise with GenAI toolchains, including LangChain, LlamaIndex, Amazon Bedrock, and multi-agent workflows.
• Deep knowledge of vector search, embeddings, retrieval pipelines, and RAG architectures, including chunking, indexing, and orchestration strategies.
• Proficiency in MLOps/LLMOps practices, including CI/CD, model and version management, observability, and monitoring production AI systems (Datadog, MLflow).
• Solid understanding of enterprise security, compliance, and data governance for AI systems, including risk, bias, and drift management.
• Knowledge of AI ethics, explainability, fairness, and bias mitigation, with the ability to embed responsible AI practices into solution design.
• Proficiency in Python, FastAPI, WebSockets, and AWS services (Lambda, S3, ECS, SageMaker).
• Excellent communication skills with the ability to translate business needs into scalable AI solutions and services.
  
  

Compensation

$150,000-$200,000 per year - Dependent on fit and experience.