Java AI Architect
$70.00 per hour
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Posted yesterday
SENIORITY
Lead
SALARY
$70.00 per hour
About the role
- 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.
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