Technical Architect - AI / ML

Position Overview

Based in California and offered as an FTE/Contract role, this position calls for a Technical Architect specializing in LLMs and Agentic AI. You will own the architecture, strategy, and delivery of enterprise-grade AI solutions, working with cross-functional teams and customers to define the AI roadmap, design scalable solutions, and ensure the responsible deployment of Generative AI across the organization.

Key Responsibilities

• Own the architecture, strategy, and delivery of enterprise-grade AI solutions ensuring scalable and secure implementations.
• Architect scalable and secure AI/ML/LLM platform solutions including data, model, and inference pipelines; establish enterprise reference architectures, reusable components, best practices, and governance standards for AI adoption; integrate cloud-native, open-source, and enterprise tools.
• Implement automated MLOps/LLMOps workflows covering deployment, monitoring, observability, compliance, and performance optimization; collaborate with cross-functional teams (engineering, data science, security, and product) to align platform capabilities with business goals and drive adoption.

Required Qualifications

• 10-16 years of experience in AI/ML-related roles with a strong focus on LLMs and Agentic AI technology.
• 6-10 years of experience in designing and implementing large-scale distributed systems, microservices, serverless, and event-driven architectures.
• 5-8 years of experience in cloud-native architecture (Azure/AWS/GCP) including networking, storage, compute scaling, GPU workloads, and managed AI services; plus experience with platform components, API design, integration patterns, and high-performance compute architecture.
• 4-7 years of experience building or integrating AI/ML platforms, pipelines, model lifecycle components, inference gateways, and/or enterprise GenAI frameworks.
• 3-6 years of experience using AI platform tools such as Databricks, Vertex AI, Azure AI Studio, AWS Bedrock, LangChain, Prompt Flow, Ray, Kubeflow, MLflow, Airflow, or Kafka.
• 2-5 years of experience designing and integrating vector database solutions such as Pinecone, Weaviate, FAISS, Milvus, Qdrant, Elastic, OpenSearch, or Cosmos DB Vector.
• 2-3 years of experience in LLM architectures, RAG pipelines & patterns, evaluation frameworks, embeddings, tokenization, prompt engineering, evaluation strategies, hallucination reduction, and Agentic AI frameworks; plus 1-2 years in Agentic AI frameworks like MCP or A2A.
• 2-3 years of experience building GenAI applications, agent workflows, or knowledge retrieval systems using frameworks like LangChain, LlamaIndex, Graph RAG, or custom implementations.
• Bachelor's or Master's degree in Computer Science, Data Science, or a related field.
• Prior experience in Agile/Scrum projects with exposure to tools like Jira or Azure DevOps.
• Strong interpersonal skills for building and maintaining productive relationships with team members and customer representatives.
• Ability to provide and receive constructive feedback during code reviews.
• An analytical mindset with the ability to translate ideas into tangible technology implementations and drive adoption.
• Robust problem-solving and analytical thinking skills with the capability to troubleshoot and resolve issues efficiently.
• Demonstrated ability to provide regular updates and communicate effectively with internal and customer stakeholders through verbal, email, and instant messaging channels.