Sr AI Architect
SunTechPros Inc.
Job Description
01. Role : Sr AI Architect
\nLocation : Raleigh NC
\nStrategic Leader who can drive and deliver multiple Al Initiatives for Clients at account level as Leader/SPOC and FDE with hands-on expertise on the below areas:
\n \nDesign end-to-end Al/ML system architecture including data pipelines, model serving, inference infrastructure, and feedback loops
\nArchitect Retrieval-Augmented Generation (RAG) pipelines for knowledge retrieval from curriculum content, textbooks, and learning repositories
\nDesign multi-modal Al systems capable of processing text, audio, video, and assessments
\nShould have hands-on exp using Claude Code, Cursor, Blitzy Platforms
\nEstablish architecture for Adaptive Learning Engines - systems that personalize content difficulty, pacing, and style based on learner behavior
\nDesign LLM orchestration layers using frameworks such as Langchain, LangGraph, AutoGen, or Semantic Kernel
\nDefine model selection and routing strategies across providers (OpenAl, Anthropic Claude, Google Gemini, AWS Bedrock, Azure OpenAl, open-source Llama/Mistral)
\nArchitect Al tutor agents capable of multi-turn dialogue, Socratic questioning, hint generation, and step-by-step explanation
\nDesign autonomous assessment agents for auto-grading, rubric evaluation, plagiarism detection, and feedback generation
\nBuild content generation pipelines for lesson plans, quiz banks, summaries, and curriculum mapping using generative Al
\nDefine and govern the Al Harness -the full agentic Al stack from input processing to output safety and observability
\nDefine multi-agent orchestration patterns for collaborative Al tasks across curriculum design, student support, and institutional reporting
\nEstablish tool-use frameworks (MCP Protocol, OpenAl Function Calling) enabling agents to query databases, search content libraries, and trigger LMS workflows
\nDefine/Bulld Knowledge Graphs for EdTech domain mapping learning objectives, concepts, prerequisites, and competencies for structured curriculum reasoning
\nDesign learner memory systems tracking long-term progress, mastery levels, and knowledge gaps across sessions
\nImplement LLM evaluation frameworks using RAGAS, DeepEval to measure faithfulness, relevance, and educational accuracy
\nDefine distributed tracing with Open Telemetry across the full Al request lifecycle for latency, cost, and quality monitoring
\nPartner with instructional designers and curriculum experts to ensure Al systems align with pedagogical best practices
\nLead proof-of-concept and pilot programs for emerging Al capabilities (Adaptive learning system)
\nDefine and maintain the Al architecture roadmap, ensuring alignment with business goals and EdTech product strategy
\nShould have experience working with neo4j, IRT based ML models, AWS Al services, Postgres, Edtech systems, AWS AgentCore, AWS Sagemaker and etc.
\n$139.4k - $230k
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