
Job Overview:
As a Technical Lead, you will be responsible for leading the design, development, and deployment of AI-powered Edtech solutions. You will mentor a team of engineers, collaborate with data scientists, and work closely with product managers to build scalable and efficient AI systems. The ideal candidate should have 8-10 years of experience in software development, machine learning, AI use case development and product creation along with strong expertise in cloud-based architectures.
Key Responsibilities:
AI Tutor & Simulation Intelligence
- Architect the AI intelligence layer that drives contextual tutoring, retrieval-based reasoning, and fact-grounded explanations.
- Build RAG (retrieval-augmented generation) pipelines and integrate verified academic datasets from textbooks and internal course notes.
- Connect the AI Tutor with the Simulation Lab, enabling dynamic feedback — the system should read experiment results, interpret them, and explain why outcomes occur.
- Ensure AI responses remain transparent, syllabus-aligned, and pedagogically accurate.
Platform & System Architecture
- Lead the development of a modular, full-stack platform unifying courses, explainers, AI chat, and simulation windows in a single environment.
- Design microservice architectures with API bridges across content systems, AI inference, user data, and analytics.
- Drive performance, scalability, and platform stability — every millisecond and every click should feel seamless.
Reliability, Security & Analytics
- Establish system observability and monitoring pipelines (usage, engagement, AI accuracy).
- Build frameworks for ethical AI, ensuring transparency, privacy, and student safety.
- Set up real-time learning analytics to measure comprehension and identify concept gaps.
Leadership & Collaboration
- Mentor and elevate engineers across backend, ML, and front-end teams.
- Collaborate with the academic and product teams to translate physics pedagogy into engineering precision.
- Evaluate and integrate emerging tools — multi-modal AI, agent frameworks, explainable AI — into the product roadmap.
Qualifications & Skills:
- 8–10 years of experience in software engineering, ML systems, or scalable AI product builds.
- Proven success leading cross-functional AI/ML and full-stack teams through 0→1 and scale-up phases.
- Expertise in cloud architecture (AWS/GCP/Azure) and containerization (Docker, Kubernetes).
- Experience designing microservices and API ecosystems for high-concurrency platforms.
- Strong knowledge of LLM fine-tuning, RAG pipelines, and vector databases (Pinecone, Weaviate, etc.).
- Demonstrated ability to work with educational data, content pipelines, and real-time systems.
Bonus Skills (Nice to Have):
- Experience with multi-modal AI models (text, image, audio, video).
- Knowledge of AI safety, ethical AI, and explain ability techniques.
- Prior work in AI-powered automation tools or AI-driven SaaS products.

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- What information we collect during our application and recruitment process and why we collect it;
- How we use that information; and
- How to access and update that information.
This policy covers the information you share with Skit (Cyllid Technologies Pvt. Ltd.) during the application or recruitment process including:
- Your name, address, email address, telephone number and other contact information;
- Your resume or CV, cover letter, previous and/or relevant work experience or other experience, education, transcripts, or other information you provide to us in support of an application and/or the application and recruitment process;
- Information from interviews and phone-screenings you may have, if any;
- Details of the type of employment you are or may be looking for, current and/or desired salary and other terms relating to compensation and benefits packages, willingness to relocate, or other job preferences;
- Details of how you heard about the position you are applying for;
- Reference information and/or information received from background checks (where applicable), including information provided by third parties;
- Information about your educational and professional background from publicly available sources, including online, that we believe is relevant to your application or a potential future application (e.g. your LinkedIn profile); and/or
- Information related to any assessment you may take as part of the interview screening process.
Your information will be used by Skit for the purposes of carrying out its application and recruitment process which includes:
- Assessing your skills, qualifications and interests against our career opportunities;
- Verifying your information and carrying out reference checks and/or conducting background checks (where applicable) if you are offered a job;
- Communications with you about the recruitment process and/or your application(s), including, in appropriate cases, informing you of other potential career opportunities at Skit;
- Creating and/or submitting reports as required under any local laws and/or regulations, where applicable;
- Making improvements to Skit's application and/or recruitment process including improving diversity in recruitment practices;
- Proactively conducting research about your educational and professional background and skills and contacting you if we think you would be suitable for a role with us.
We collect and process some or all of the following types of information from you:
- Information that you provide when you apply for a role. This includes information provided through an online job site, via email, in person at interviews and/or by any other method.
- In particular, We process personal details such as name, email address, address, telephone number, date of birth, qualifications, experience, information relating to your employment history, skills experience that you provide to Us, as well as your video in case you conduct your interview using the Video Interview feature.
- If you contact Us, We may keep a record of that correspondence.
- A record of your progress through any hiring process that we may conduct.
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