Java AI Architect

Rate: $70/hr.

Location: Remote

Duration: 6 months

Job Description: See below: Must Have Technical/Functional Skills:· Proven experience as an AI Architect defining enterprise AI architecture, standards, and governance.· Hands-on experience designing/building agent-based approaches and autonomous workflows.· Strong expertise in Prompt Engineering (Zero/Few-shot, Chain-of-Thought) and prompt design.· Strong Python development experience and ability to guide teams with reference implementations.· Experience with RAG, vector databases, and cloud deployments.· Practical experience with GitHub Copilot adoption patterns including guardrails, prompt library management, extensions, and metrics Preferred / Nice to Have· Experience designing enterprise adoption frameworks for Copilot/AI with change management and champion models.· Experience building Copilot-led accelerators for engineering productivity and rapid prototyping.· Knowledge of AI governance requirements and productionization practices. Roles & Responsibilities1) Architecture & Strategy (AI / Agentic AI)· Define the overall solution architecture for enterprise agentic AI programs and create the target-state roadmap· Establish AI architecture standards, reference patterns, and governance guidelines for adoption at scale.· Design architecture across LLMs/frameworks, vector databases, and cloud deployments, including Responsible AI practices.2) Autonomous Agent Design & Orchestration (Copilot-led)· Architect and enable autonomous agent workflows using GitHub Copilot, including multi-step orchestration and enterprise guardrails.· Define a framework for prompt libraries, guardrails, extensions/integrations, and productivity metric tracking for Copilot adopt· Drive repeatable implementation approach and best practices for Copilot-based engineering interventions and productivity tracking· Enable Copilot-driven acceleration from design artifacts (e.g., Figma requirement sheets) to boilerplate code and supporting assets, where applicable.· Establish patterns for agent-assisted testing and a roadmap toward autonomous testing where feasible (e.g., test case generation, script automation, regression maintenance).3) Prompt Engineering Excellence· Own enterprise prompt strategy including Zero-shot / Few-shot / Chain-of-Thought prompting techniques and prompt governance.· Create reusable prompt frameworks/cookbooks, templates, and standards for consistent outcomes across teams.4) RAG + Model/Tool Orchestration (Python-led)· Architect and govern RAG pipelines, knowledge grounding approaches, and multi-turn agent orchestration using frameworks such as LangChain (or equivalent).· Provide hands-on guidance for implementation in Python, including reference implementations and integration patterns.