Role: Principal or Senior / AI Solution Architect
Location: REMOTE
Experience: 20+
Duration: Long Term Project
Client: Capgemini/End client
Job Role and Responsibilities:
The AI Solution Architect serves as the technical authority and strategic advisor across all priority use cases. This person provides end-to-end architectural oversight, ensures design consistency across delivery teams, and bridges the gap between the AI Foundry''s reusable platform services and actual production delivery. The role requires making Go/No-Go decisions on architecture and guiding multiple partner teams toward aligned, scalable solutions.
2 Key Responsibilities
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Embed with the client AI team to gain full understanding of all priority use cases and current architecture
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Assess current technical approaches across multiple delivery partners and identify coordination gaps
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Define and enforce standard AI architecture patterns across use cases (model selection, RAG pipelines, chunking, orchestration)
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Identify and eliminate duplicate components; mandate consolidation into reusable services
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Provide technical visibility and recommendations to Gas Power executive leadership
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Participate in PI Planning sessions and monthly executive reviews
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Define observability, evaluation, and monitoring frameworks (latency, accuracy, hallucination tracking, cost)
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Upskill delivery partner teams on validated architectural patterns and best practices
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Own cost efficiency of AI solutions by influencing design choices (model usage, token optimization, retrieval strategies)
3 Required Qualifications
Technical Requirements
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10+ years in solution architecture with 3 to 5 years focused on AI/ML solutions
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Deep expertise in Generative AI architecture: RAG pipelines, agentic frameworks, LLM orchestration, multi-agent systems
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Proven ability to design scalable, reusable AI patterns applicable across multiple use cases and teams
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Experience addressing prompt brittleness, chunking strategies, hybrid retrieval methods (semantic + keyword), and re-ranking
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Experience evaluating platform/foundry reusable services and making fit-for-purpose vs. technical debt determinations
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T-shaped expertise: deep in AI solution architecture with breadth across data architecture, integration, and infrastructure
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Experience with enterprise data platforms (Databricks, SharePoint, ERP systems) and integration patterns
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Knowledge of observability and evaluation frameworks for AI systems
Advisory and Leadership Requirements
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Demonstrated experience in a strategic advisory capacity, not solely implementation
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Track record of working across multiple delivery partners simultaneously in enterprise settings
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Executive communication skills, able to present to VP/Sr. Director-level stakeholders
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Influence without authority, able to guide partner delivery teams without direct management
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Coaching and mentoring experience, actively developing junior and mid-level architects
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Ability to navigate organizational complexity, political dynamics, and multi-team coordination
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Experience translating ambiguous objectives into structured action plans
4 Specific Technical Focus Areas
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RAG pipeline architecture: chunking, embedding models, hybrid search, retrieval optimization
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Agentic AI orchestration patterns and multi-agent coordination
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Non-sequential document context extraction (critical for document-heavy use cases)
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Model selection strategy and token/cost optimization
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Standardized integration patterns with enterprise data systems
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Architecture governance: defining and enforcing patterns across independent delivery teams
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Shahid Shaikh
Senior Lead Technical Recruiter |
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2050 Center Avenue | Suite 600 | Fort Lee, NJ 07024
Email: shahid.m@wonese.comÂ
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