AI Solution Architect

A Strategic Leader who can drive and deliver multiple AI Initiatives for Clients at account level as Leader/SPOC and FDE with hands-on expertise on the below areas: Design end-to-end AI/ML system architecture including data pipelines, model serving, inference infrastructure, and feedback loops. Establish tool-use frameworks (MCP Protocol, OpenAI Function Calling) enabling agents to query databases, search content libraries, and trigger LMS workflows.

Our Client, an IT Services and Consultant company, is looking for an AI Solution Architect for their Durham, NC/Hybrid location.
 
Responsibilities:

• A Strategic Leader who can drive and deliver multiple AI Initiatives for Clients at account level as Leader/SPOC and FDE with hands-on expertise on the below areas:
• Design end-to-end AI/ML system architecture including data pipelines, model serving, inference infrastructure, and feedback loops
• Architect Retrieval-Augmented Generation (RAG) pipelines for knowledge retrieval from curriculum content, textbooks, and learning repositories
• Design multi-modal AI systems capable of processing text, audio, video, and assessments - Should have hands-on exp using Claude Code, Cursor, Blitzy Platforms
• Establish architecture for Adaptive Learning Engines — systems that personalize content difficulty, pacing, and style based on learner behavior
• Design LLM orchestration layers using frameworks such as Langchain, LangGraph, AutoGen, or Semantic Kernel
• Define model selection and routing strategies across providers (OpenAI, Anthropic Claude, Google Gemini, AWS Bedrock, Azure OpenAI, open-source Llama/Mistral)
• Architect AI tutor agents capable of multi-turn dialogue, Socratic questioning, hint generation, and step-by-step explanation
• Design autonomous assessment agents for auto-grading, rubric evaluation, plagiarism detection, and feedback generation
• Build content generation pipelines for lesson plans, quiz banks, summaries, and curriculum mapping using generative AI
• Define and govern the AI Harness — the full agentic AI stack from input processing to output safety and observability
• Define multi-agent orchestration patterns for collaborative AI tasks across curriculum design, student support, and institutional reporting
• Establish tool-use frameworks (MCP Protocol, OpenAI Function Calling) enabling agents to query databases, search content libraries, and trigger LMS workflows
• Define/Build Knowledge Graphs for EdTech domain mapping learning objectives, concepts, prerequisites, and competencies for structured curriculum reasoning
• Design learner memory systems tracking long-term progress, mastery levels, and knowledge gaps across sessions
• Implement LLM evaluation frameworks using RAGAS, DeepEval to measure faithfulness, relevance, and educational accuracy
• Define distributed tracing with Open Telemetry across the full AI request lifecycle for latency, cost, and quality monitoring
• Partner with instructional designers and curriculum experts to ensure AI systems align with pedagogical best practices
• Lead proof-of-concept and pilot programs for emerging AI capabilities (Adaptive learning system)
• Define and maintain the AI architecture roadmap, ensuring alignment with business goals and EdTech product strategy

 
Requirements:

• Should have experience working with neo4j, IRT based ML models, AWS AI services, Postgres, Edtech systems, AWS AgentCore, AWS Sagemaker and etc.
• AI Solution Architect
• Agentic AI
• AI/ML
• Years of experience required: 15-20

 
Why Should You Apply?

• Health Benefits
• Referral Program
• Excellent growth and advancement opportunities