Java AI Architect

AI Architect

Visa not allowed.

• CPT EAD
• Stem – OPT
• OPT EAD
• FTE to Subco conversion – 6 months cooling period we need to follow or get approval.

• Atos has stringent compliance and security requirements that all employees are expected to adhere to.
• Inform the candidate that they must not have any other part-time or full-time employment while working with Atos on this assignment.
• Obtain explicit confirmation from the candidate that they understand and are comfortable with these requirements and the expected work arrangement before proceeding further.

• Client Name:
  Digital Practice – Internal Customer
• Posman
• Position :
• Job Posting P
• Role/
  
  Skills:
  
  Java EE, React JS, MSGithub Copilot
• 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 Git Hub 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 & Responsibilities

1) 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 Git Hub 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 Lang Chain (or equivalent).

· Provide hands-on guidance for implementation in Python, including reference implementations and integration patterns.