Company Name: American IT Systems

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Job Url: https://www.indeed.com/viewjob?cmp=American-IT-Systems&t=Senior+Ai+Architect&jk=ac47c550592a8765&q=Ai&xpse=SoDc67I3sNv3T_WEqZ0LbzkdCdPP&xfps=d04d1caa-ff6a-4937-9e9d-310438d43498&xkcb=SoAV67M3sNvsojzb9Z0ObzkdCdPP&vjs=3

Job Description: Role: Senior AI Architect – AI, GenAI & Agentic AI (with Context Engineering Expertise)
Location: Remote- USA only
Role Overview
We are looking for a Senior AI Architect to guide enterprise customers through current-state vs future-state AI transformations.
The ideal candidate has deep expertise in context engineering—designing and orchestrating context-aware AI systems—and a proven track record of building enterprise-grade AI, GenAI, and Agentic AI solutions.
This role blends strategic advisory (gap analysis, roadmaps, executive communication) with hands-on technical architecture (context pipelines, orchestration frameworks, and governance).
Key Responsibilities
Advisory & Gap Analysis
 Conduct AI maturity and readiness assessments, covering infrastructure, data, model lifecycle, and context engineering practices.
 Perform gap analysis of current-state AI/GenAI systems vs desired future-state capabilities (e.g., from single-model solutions to context-rich multi-agent ecosystems).
 Recommend AI adoption roadmaps aligned with business outcomes, ROI, and compliance needs.
 Context Engineering & AI Enablement
 Architect context engineering frameworks that unify structured, semi-structured, and unstructured enterprise knowledge into usable context for LLMs and agentic systems.
 Build real-time context pipelines (ingestion, enrichment, retrieval, orchestration) to reduce latency and improve accuracy.
 Define context interfaces/APIs to enable consumption of enterprise knowledge across AI agents, applications, and workflows.
 Implement guardrails, policy layers, and context redaction modules to ensure security, compliance, and ethical AI usage.
 Enterprise-Grade AI Architecture
 Design scalable architectures for AI/GenAI/Agentic AI across cloud and hybrid environments (AWS, Azure, GCP).
 Integrate LLMs with vector databases, knowledge graphs, and real-time context stores.
 Lead multi-agent system design (LangGraph, MCP, AutoGen, custom orchestration) to enable autonomous workflows.
 Ensure compliance with enterprise governance frameworks (HIPAA, FDA, GDPR, Part 11/820, HITRUST).
 Strategy, Innovation & Customer Advisory
 Run executive workshops and clearly articulate the value of context-aware AI architectures.
 Build maturity models for context engineering adoption and measure business impact.
 Stay ahead of the curve in Agentic AI, contextual orchestration, and self-healing AI systems.
 Contribute to whitepapers, thought leadership, and reference architectures for enterprise customers.

Qualifications & Experience
Education: Bachelor’s/master’s in computer science, AI/ML, Data Science, or related; PhD a plus.
Experience:
5+ years in AI/ML and enterprise architecture and 10+ years of overall experience needed
3+ years with LLMs, GenAI platforms, and orchestration frameworks.
Proven ability to lead context engineering initiatives in large enterprises.
Technical Expertise:
Context Engineering: pgvector, Pinecone, Redis, Weaviate, Milvus, knowledge graphs, context layering techniques.
AI/GenAI: OpenAI, Anthropic, LLaMA, Hugging Face, fine-tuning, RAG pipelines, policy/guardrail frameworks.
Agentic AI: LangChain, LangGraph, MCP, AutoGen, custom orchestration.
Enterprise Systems: Integrations with ERP, CRM, EMR/EHR, ServiceNow, etc.
MLOps & Governance: MLflow, Kubeflow, ModelOps pipelines, Responsible AI frameworks, explainability tools (SHAP, LIME).
Key Competencies
Visionary strategist who can map current-state vs future-state AI for enterprises.
Hands-on architect with experience building context-aware, real-time AI ecosystems.
Strong executive advisory skills with ability to influence at CxO level.
Ability to balance innovation with compliance in regulated industries.
Job Type: Contract
Pay: $60.00 - $70.00 per hour
Work Location: Remote