GeniWay Technologies

About GeniWay

GeniWay Technologies is building AI-powered products that help students learn effectively and make confident education and career decisions.

Our first product, Clario, combines multidimensional student assessment, career intelligence, personalized guidance, and AI-assisted counselling for Indian students and families.

With Clario’s initial platform nearing completion, our next major ambition is to build an AI-powered personalized learning platform that adapts learning experiences to each student’s knowledge, goals, learning patterns, motivation, and progress.

We are looking for an AI-native engineering leader to help turn this ambition into a trusted, scalable product.

The Opportunity

We are hiring a Founding AI Engineering Lead, CTO Track to become GeniWay’s full-time technical operating leader.

Your primary mandate will be to lead the engineering of our AI-powered personalized learning platform. You will also own the continued evolution, reliability, and scale-readiness of Clario.

This is not a conventional engineering management role or a role limited to integrating third-party AI APIs. It requires someone who can combine:

• deep applied-AI expertise;
• strong product and architectural judgment;
• hands-on full-stack engineering;
• engineering-team leadership; and
• responsible deployment of AI for students.

For an exceptional leader who demonstrates sustained company-level technology leadership, this role offers a credible pathway toward becoming GeniWay’s future CTO.

What You Will Build

The personalized learning platform is expected to progressively support:

• continuously evolving learner profiles;
• personalized learning pathways and interventions;
• adaptive content, practice, and assessments;
• AI tutors, mentors, and learning companions;
• multi-agent workflows for learning support and content operations;
• student progress, mastery, and engagement intelligence;
• evidence-grounded recommendations for students, parents, and educators;
• responsible human oversight, safety, and explainability.

You will help define the architecture, technical strategy, and delivery roadmap required to build these capabilities responsibly.

What You Will Own

AI Product and Platform Engineering

• Own the architecture and engineering of GeniWay’s personalized learning platform.
• Translate learning-product concepts into reliable AI-powered experiences.
• Design and build GenAI, agentic-AI, and ML-enabled workflows.
• Determine when to use LLMs, deterministic logic, retrieval, conventional ML, or human review.
• Build reusable AI-platform capabilities instead of isolated prompt-based features.
• Lead experimentation, evaluation, production deployment, and continuous improvement of AI capabilities.

Applied AI Quality and Safety

• Establish evaluation frameworks for accuracy, relevance, personalization, consistency, latency, and cost.
• Design safeguards against hallucinations, unsafe guidance, bias, prompt injection, and inappropriate student interactions.
• Build observability and feedback loops for AI behaviour in production.
• Ensure student-facing AI systems are explainable, privacy-conscious, age-appropriate, and human-supervised where required.
• Work with product and domain specialists to validate educational usefulness, not merely technical performance.

Product Engineering and Delivery

• Own end-to-end engineering delivery across AI, backend, frontend, data, and infrastructure.
• Lead or personally implement critical product capabilities when required.
• Establish predictable planning, development, testing, release, and incident-management practices.
• Scale and strengthen Clario while building the next product platform.
• Balance speed, product quality, maintainability, scalability, and operating cost.

Architecture and Data Foundations

• Define and evolve the application, AI, data, and cloud architecture.
• Build secure foundations for learner profiles, content intelligence, personalization, and analytics.
• Establish effective data pipelines, model interfaces, APIs, and platform services.
• Make pragmatic build-versus-buy and model-selection decisions.
• Reduce technical debt and material technology risks systematically.

Team and Technology Leadership

• Lead, mentor, and raise the effectiveness of the engineering team.
• Build strong AI and software-engineering practices across the organization.
• Help recruit future AI, data, and product engineers.
• Work closely with the Founder on product strategy, priorities, and technology investments.
• Develop GeniWay’s longer-term technology strategy and engineering organization.

Essential Capabilities

• Strong hands-on experience building and operating AI-powered products in production.
• Deep practical understanding of GenAI application architecture, LLM behaviour, prompting, context engineering, and structured outputs.
• Experience building agentic or multi-step AI workflows with appropriate controls and observability.
• Experience with retrieval-augmented generation, embeddings, semantic search, or knowledge systems.
• Ability to evaluate AI quality systematically rather than relying on subjective demonstrations.
• Strong Python, backend, API, database, and system-design capabilities.
• Ability to lead full-stack product engineering beyond the AI layer.
• Experience leading engineers and owning complex product delivery.
• Strong product judgment and ability to translate ambiguous goals into executable plans.
• High ownership, urgency, reliability, and transparent communication.

Strongly Preferred

• Experience building personalization, recommendation, adaptive-learning, tutoring, or conversational-AI products.
• Practical AI/ML experience involving experimentation, feature engineering, model evaluation, or predictive systems.
• Experience with LLMOps or MLOps, including evaluation, monitoring, versioning, and deployment.
• Experience designing AI guardrails and responsible student-facing systems.
• Experience as a founding engineer, technical lead, or early engineering leader.
• Experience building AI-native products from zero to one.
• Interest in learning science, education, and student outcomes.

What We Are Not Looking For

• A pure people manager who is no longer technically hands-on.
• A research-only AI specialist without strong product-engineering capability.
• Someone whose GenAI experience is limited to basic chatbot or API integrations.
• A generalist engineering leader with little evidence of applied-AI delivery.
• An advisor seeking influence without full-time operating accountability.

What Success Looks Like

First 90 Days

• Take operational ownership of GeniWay’s engineering function.
• Understand and strengthen Clario’s architecture, quality, and scale-readiness.
• Define the technical architecture and phased roadmap for the personalized learning platform.
• Establish AI evaluation, safety, engineering-quality, and release practices.
• Improve team accountability, execution rhythm, and delivery predictability.

First 6-9 Months

• Deliver the first meaningful version of the personalized learning platform.
• Establish reusable foundations for learner modelling, personalization, AI agents, evaluation, and observability.
• Demonstrate measurable educational and product value from AI capabilities.
• Build a dependable engineering and AI delivery organization.
• Demonstrate readiness for broader CTO-level responsibility.

Compensation and Growth

• Fixed compensation: ₹20L–₹25L per annum, based on capability and experience
• Performance-linked variable: Up to 15%–20%, tied to agreed outcomes
• Initial ESOP grant: Approximately 0.75%–1.25%, based on fit and expected ownership
• Leadership equity top-up: Potential additional 0.5%–1% after 12–18 months, based on sustained contribution and evolution toward CTO-level responsibility
• Leadership review: Formal assessment after six months, followed by a broader role and compensation review after 12 months

The CTO pathway is earned through demonstrated technology strategy, AI-product leadership, organizational impact, and company-level ownership.

Selected candidates will complete structured discussions covering applied-AI depth, architecture, hands-on engineering, product judgment, responsible AI, leadership approach, and long-term alignment.