[Hiring] Agentic AI Architect @Trekai

Role Description

TrekAI is reinventing education through AI. As a high-growth, mission-driven startup, we build technology that directly impacts teachers, students, and school systems.

As TrekAI’s Agentic AI Architect, you will drive the design, development, and deployment of the models, algorithms, and policies that power adaptive, personalized, and explainable learning experiences. Partnering closely with the CTO and the Director of Engineering, you will help shape TrekAI’s AI strategy and long-term IP vision while collaborating with product and engineering leadership to bring scalable, production-grade AI systems into real classrooms. This is a rare opportunity to help pioneer next-generation agentic learning systems and transform cutting-edge AI research into impactful educational outcomes.

Key Responsibilities

• Lead TrekAI’s AI technology strategy, defining the end-to-end architecture for multi-agent reasoning, retrieval-augmented generation (RAG), and causal inference pipelines.
• Design and orchestrate multi-agent or agentic architectures that deliver measurable improvements in teaching productivity and student mastery velocity.
• Advance automated reasoning using GenAI/LLMs, causal systems — optimizing for low latency, safe outputs, and learning outcome alignment.
• Define and own the data strategy — transcripts, curriculum standards, chat interactions, feature stores, experimentation frameworks, and model retraining pipelines.
• Ensure fairness, transparency, and explainability using causal inference, counterfactual analysis, and model interpretability frameworks.
• Partner with UX and product to define teacher/student-facing interventions; work with DevOps & Systems Architect to production deploy models with CI/CD, monitoring, and observability.

Qualifications

• Education: PhD or MS in Computer Science, Data Science, Machine Learning, or related field.
• Leadership: 10+ years in ML/AI leadership, with a proven record of taking models from research → production at scale.
• GenAI / LLM Platforms: Hands-on with OpenAI (GPT), Google Gemini, Anthropic Claude, Mistral, Llama, or open-source LLM fine-tuning (LoRA/QLoRA, PEFT).
• Agentic Platforms: Demonstrated experience building harnesses with first party SDKs/APIs to build agents or experience with agentic frameworks such as LangGraph, Autogen, CrewAI, or LlamaIndex (or equivalent) to build multi-agent reasoning or workflow orchestration systems.
• RL / DRL Frameworks: Familiarity with Ray RLlib, Stable Baselines3, CleanRL, TRL (HuggingFace), or custom policy-gradient implementations for bandit/RLHF/RLAIF pipelines.
• Causal AI Knowledge: Skilled with DoWhy, CausalML, SCM frameworks for counterfactuals, interventions, and causal inference applied to education data.
• Solid programming and DB skills: Python, React, Node.js, Java, Json, SQL, NoSQL.
• MLOps & Production: Experience deploying ML systems with CI/CD, monitoring (Prometheus/Grafana, Sentry, PostHog), model versioning, and drift detection.
• Track Record: Proven success delivering commercially impactful AI products, ideally in EdTech or learning platform domains (a strong plus).
• Startup experience is preferred.

Bonus Points

• Passion for transforming education and closing equity gaps.
• Experience balancing innovation with model safety, bias mitigation, and regulatory compliance (FERPA, COPPA, GDPR).