Engineering Manager

high-ownership environments

shape the product, scale the platform, influence the engineering culture, and lead a team that builds with heart and hustle.

As an Engineering Manager here, you will:

• Lead a talented team of engineers while remaining hands-on with architecture and development.
• Champion the use of

  AI/ML

  , LLM-driven features, and intelligent systems to elevate learner experience.
• Inspire a culture of high performance, clear thinking, and thoughtful engineering.
• Partner closely with product, design, and content teams to deliver delightful, meaningful user experiences.
• Bring structure, clarity, and energy to complex problem-solving.
• This role is ideal for someone who loves

  building, mentoring, scaling

  , and thinking several steps ahead.

Technical Leadership & Ownership

• Lead end-to-end development across backend, frontend, architecture, and infrastructure in partnership with product and design teams.
• Stay hands-on with the

  MERN stack

  ,

  Python

  , and

  AI/ML technologies

  , while guiding and coaching a high-performance engineering team.
• Architect, develop, and maintain

  distributed microservices

  ,

  event-driven systems

  , and robust APIs on AWS.

AI/ML Engineering

• Build and deploy

  AI-powered features

  , leveraging LLMs, RAG pipelines, embeddings, vector databases, and model evaluation frameworks.
• Drive prompt engineering, retrieval optimization, and continuous refinement of AI system performance.
• Champion the adoption of modern AI coding tools and emerging AI platforms to boost team productivity.

Cloud, Data, DevOps & Scaling

• Own deployments and auto-scaling on AWS (ECS, Lambda, CloudFront, SQS, SES, ELB, S3).
• Build and optimize real-time and batch data pipelines using

  BigQuery

  and other analytics tools.
• Implement CI/CD pipelines for Dockerized applications, ensuring strong observability through

  Prometheus, Loki, Grafana, CloudWatch

  .
• Enforce best practices around security, code quality, testing, and system performance.

Collaboration & Delivery Excellence

• Partner closely with product managers, designers, and QA to deliver features with clarity, speed, and reliability.
• Drive agile rituals, ensure engineering predictability, and foster a culture of ownership, innovation, and continuous improvement

Required Skills & Experience

• 8–12 years

  of experience in full-stack or backend engineering with at least

  5+ years leading engineering teams

  .
• Strong hands-on expertise in the

  MERN stack

  and modern JavaScript/TypeScript ecosystems.

• 5+ years

  building and scaling production-grade applications and distributed systems.

• 2+ years

  building and deploying

  AI/ML products

  — including training, tuning, integrating, and monitoring AI models in production.
• Practical experience with

  SQL, NoSQL, vector databases

  , embeddings, and production-grade

  RAG systems

  .
• Strong understanding of

  LLM prompt optimization

  , evaluation frameworks, and AI-driven system design.
• Hands-on with AI developer tools, automation utilities, and emerging AI productivity platforms.

Preferred Skills

• Familiarity with

  LLM orchestration frameworks

  (LangChain, LlamaIndex, etc.) and advanced tool-calling workflows.
• Experience building

  async workflows

  , schedulers, background jobs, and offline processing systems.
• Exposure to modern

  frontend testing frameworks

  , QA automation, and performance testing.

What You’ll Love Here

1. The chance to build

   AI-powered capabilities

   for impact at national scale.
2. A team that celebrates initiative, creativity, and experimentation.
3. A product with purpose — improving futures, not just metrics.
4. Freedom to try, fail, iterate, and try again.
5. A work culture where your ideas matter and your ownership is real.