WinWire

Technical Architect - AI / ML

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is a Technical Architect - AI/ML in California, available as a contract with a pay rate of "X". Requires 10-16 years in AI/ML, expertise in LLMs, cloud architecture (Azure/AWS/GCP), and experience with AI platform tools.
🌎 - Country
United States
πŸ’± - Currency
Unknown
-
πŸ’° - Day rate
Unknown
-
πŸ—“οΈ - Date
January 8, 2026
πŸ•’ - Duration
Unknown
-
🏝️ - Location
Unknown
-
πŸ“„ - Contract
Unknown
-
πŸ”’ - Security
Unknown
-
πŸ“ - Location detailed
San Jose, CA
-
🧠 - Skills detailed
#Azure #DevOps #Storage #Cloud #API (Application Programming Interface) #Jira #MLflow #Strategy #Azure DevOps #Kafka (Apache Kafka) #Code Reviews #GCP (Google Cloud Platform) #OpenSearch #Airflow #Computer Science #Data Science #Microservices #Databricks #Scrum #Langchain #Monitoring #Security #AI (Artificial Intelligence) #Agile #AWS (Amazon Web Services) #Databases #Compliance #Scala #Observability #Deployment #ML (Machine Learning)
Role description
Location : California Job Type : FTE/Contract Job Description : As a Technical Architect specializing in LLMs and Agentic AI, you will own the architecture, strategy, and delivery of enterprise-grade AI solutions. Work with cross-functional teams and customers to define the AI roadmap, design scalable solutions, and ensure responsible deployment of Generative AI across the organization. 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 such as vector databases, feature stores, registries, and orchestration frameworks 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 10–16 years of experience in AI/ML-related roles, with a strong focus on LLM’s & 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 experience in Azure / AWS / GCP including networking, storage, compute scaling, GPU workloads, and managed AI services; 5-8 years of 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, Kafka, etc. 2-5 years of experience in designing and integrating vector database solutions such as Pinecone, Weaviate, FAISS, Milvus, Qdrant, Elastic, OpenSearch, 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, multi agent orchestrations and frameworks; 1-2 years of experience in Agentic AI frameworks, MCP, 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 working on Agile/Scrum projects with exposure to tools like Jira/Azure DevOps Strong interpersonal skills to build and maintain productive relationships with team members & customer reps Provide constructive feedback during code reviews and be open to receiving feedback on your own code Analytical mindset; Ability to bring idea into reality through technology implementation & adoption Problem-Solving and Analytical Thinking; Capability to troubleshoot and resolve issues efficiently Provides regular updates, proactive and due diligent to carry out responsibilities; Communicate effectively with internal and customer stakeholders; Communication approach: verbal, emails and instant messages