About the Role:

As the Head of Engineering, you will be responsible for building scalable data pipelines, backend services, and cloud infrastructure to power our AI-driven platform, leading the entire engineering team, and helping founders foster a high-performance engineering culture with best coding practices, documentation, and DevOps workflows.

Total Experience: 5-10 years

Key Responsibilities:

Tech Leadership & Strategy:

- Lead backend, data engineering, and infrastructure efforts, ensuring scalability and reliability.

- Drive microservices architecture and serverless implementations on AWS.

- Collaborate with AI engineers to integrate LLM-powered features efficiently.

Backend & Data Engineering:

- Architect and develop high-performance APIs using Django & NodeJS.

- Build scalable ETL pipelines to collect, clean, and update university and course data.

- Work with RDS, DynamoDB, and MongoDB for structured and unstructured data management.

Cloud & DevOps:

- Implement CI/CD pipelines, containerization (Docker, Kubernetes), and AWS infrastructure (Lambda, API Gateway, ALB, Amplify etc.).

- Ensure scalability, security, and cost efficiency of cloud infrastructure.

- Automate deployments and optimize system performance.

Team Leadership & Growth:

- Lead and mentor backend and DevOps engineers.

- Foster a high-performance engineering culture with best coding practices, documentation, and DevOps workflows.

What makes you a great fit?:

- 3-4 years of experience in backend development, data engineering, and cloud infrastructures.

- Ability to work in a fast-paced startup environment and make key architectural decisions.

- Expertise in Python (Django) and Node.js (Nest.js) for backend development.

- Strong experience with AWS (Lambda, API Gateway, RDS, DynamoDB, CI/CD, Microservices, DevOps).

- Experience building ETL pipelines and managing large datasets for AI-powered applications.

- Hands-on knowledge of infrastructure as code (Terraform, AWS CDK) and containerization (Docker/Kubernetes) is preferred.

- Experience working with AI/ML teams, particularly in RAG and LLM fine-tuning workflows, is a plus.

Why Join Us?:

You will build a category, not a feature:

Admissions is a broken multi-billion-dollar industry, and we are rebuilding it from first principles with data, velocity, and craftsmanship, offering a once-in-a-decade chance to define a new default.

You own the technical vision end-to-end:

From architecture to infra to velocity to culture, you are not inheriting a messy legacy stack; you are defining the blueprint for the entire engineering team.

Your impact is immediate and personal:

You will ship a feature and literally see someones life trajectory change in real time, a feedback loop that is rare and unforgettable.

You hate slowness, love the fast-paced culture:

Your systems define how fast we diagnose, fix, and scale, and you get to set the unreasonable pace because if you move at 10x, Ambitio moves at 10x.