Job Title: AI Architect (Agentic Solutions)

Location: Remote
Duration: Long-Term Contract
Pay Rate: $60–$65/hr. on W2

Experience Required

• 10+ years of overall engineering experience.

• 4+ years of experience delivering AI agents and agentic solutions into production.

Job Description

We are looking for an experienced AI Architect specializing in Agentic Solutions to own the technical specifications, system architecture, and governance of enterprise AI solutions.

The ideal candidate will translate business requirements into approved technical specifications, design scalable AI systems, establish guardrails, and define evaluation strategies. The role will involve directing engineering teams using AI-powered coding agents and ensuring solutions meet architectural, quality, security, and compliance standards before production release.

Key Responsibilities

• Collaborate with Product Owners to refine business epics, break them into testable user stories, and define acceptance criteria.

• Develop technical specifications using AI agents and evaluate architectural design options.

• Select appropriate Microsoft Azure AI technologies, including Copilot Studio, Azure AI Foundry Agents, and Microsoft Agent Framework.

• Design end-to-end AI architectures covering:

  • Retrieval-Augmented Generation (RAG): Chunking, indexing, hybrid search, reranking, grounding, and citations.

  • Multi-Agent Architecture: Agent orchestration, tool contracts, handoffs, and failure handling.

  • LLM Management: Model selection, routing, fallbacks, retries, caching, rate limits, and structured outputs.

  • Token and Cost Optimization: Context budgets, prompt compression, model tiering, and cost-per-transaction management.

  • Decision APIs: Integration of deterministic business rules and decision services.

• Define document intelligence, vector database, retrieval, and context engineering strategies.

• Establish AI guardrails covering business rules, data access, human approval workflows, responsible AI, and compliance.

• Define AI evaluation strategies, including test datasets, performance metrics, acceptance thresholds, and release criteria.

• Establish observability standards covering traces, logs, metrics, and alerts for AI agents.

• Design and manage A/B testing for prompts, models, and retrieval improvements.

• Review architectural alignment during pull requests and validate evaluation evidence.

• Approve release gates and provide architectural sign-off before production deployment.

• Maintain reusable architectural patterns, templates, prompts, and technical documentation.

Required Qualifications & Technical Skills

1. AI & Agentic Architecture

• Proven experience delivering production-grade agentic AI and LLM solutions.

• Strong expertise in tool calling, orchestration, RAG, and multi-agent architectures.

2. Microsoft AI & Azure Technologies

• Azure AI Foundry

• Microsoft Copilot Studio

• Microsoft Agent Framework

• Azure OpenAI

• Azure AI Search

• Microsoft Entra ID

• Azure Security

3. Document Intelligence & Retrieval

• Experience with Azure AI Document Intelligence or equivalent platforms.

• Expertise in document layout extraction, table extraction, scanned document processing, and low-quality record handling.

• Experience implementing field-level confidence scoring and validation.

• Strong understanding of vector databases, embedding models, indexing, chunking, hybrid search, and retrieval quality measurement.

4. Context Engineering & LLM Optimization

• Experience managing instructions, retrieved information, memory, and tool outputs within token budgets.

• Expertise in prompt optimization, context assembly, model routing, and cost management.

5. AI Evaluation & Responsible AI

• Experience with golden datasets, LLM-as-a-Judge, and human evaluation.

• Knowledge of groundedness, relevance, accuracy, and AI safety metrics.

• Experience implementing regression evaluations in CI/CD pipelines.

• Ability to define business-approved evaluation thresholds and release criteria.

6. Observability & Experimentation

• Experience with OpenTelemetry instrumentation, including traces, spans, metrics, and logs.

• Familiarity with Azure Monitor and Application Insights or equivalent tools.

• Ability to monitor latency, token consumption, cost, and production quality.

• Experience with A/B testing, shadow testing, and rollback strategies.

7. Engineering & Enterprise Integration

• Experience with spec-driven development using AI coding agents such as GitHub Copilot and Claude Code.

• Strong understanding of enterprise integrations, APIs, event-driven architecture, batch pipelines, and CI/CD.

• Excellent written and verbal communication skills.

• Ability to translate business policies into precise, testable technical specifications and communicate architectural decisions to technical and business stakeholders.

Preferred Certifications

• Microsoft Certified: Azure AI Engineer Associate.

• Azure AI Apps and Agents Developer Associate.

• Agentic AI Business Solutions Architect.

Nice-to-Have Skills

• Experience working with US healthcare payers.

• Knowledge of claims adjudication, Medicaid, managed care, utilization management, appeals, HEDIS, and CAHPS.

• Familiarity with Facets, Edifecs, or similar healthcare payer platforms.

• Understanding of HIPAA compliance, PHI data handling, and audit-ready AI governance and controls.