Asks for

The ad says“Practical LLM orchestration and prompt engineering (LangChain or comparable), including agent/tool design, system-prompt and persona design, and guardrails.”
The ad says“An AI-native engineer who builds fluently with modern AI-assisted development tools (e.g. Cursor) and weaves AI through their workflow.”
The ad says“Strong Python and solid backend fundamentals (APIs, databases, data pipelines), with enough frontend ability to work end-to-end across the stack.”
The ad says“Solid AWS experience (compute, storage, databases, containers, monitoring); familiarity with managed model services (e.g. Amazon Bedrock) and/or self-hosted model inference is a plus.”
The ad says“Solid AWS experience (compute, storage, databases, containers, monitoring); familiarity with managed model services (e.g. Amazon Bedrock) and/or self-hosted model inference is a plus.”
The ad says“Solid AWS experience (compute, storage, databases, containers, monitoring); familiarity with managed model services (e.g. Amazon Bedrock) and/or self-hosted model inference is a plus.”
The ad says“An AI-native engineer who builds fluently with modern AI-assisted development tools (e.g. Cursor) and weaves AI through their workflow.”
The ad says“Strong Python and solid backend fundamentals (APIs, databases, data pipelines), with enough frontend ability to work end-to-end across the stack.”
The ad says“Strong Python and solid backend fundamentals (APIs, databases, data pipelines), with enough frontend ability to work end-to-end across the stack.”
The ad says“Strong experience building retrieval-augmented (RAG) systems — embeddings, vector databases, semantic search, and re-ranking — with a real feel for what makes retrieval accurate and dependable.”
The ad says“Practical LLM orchestration and prompt engineering (LangChain or comparable), including agent/tool design, system-prompt and persona design, and guardrails.”
The ad says“Practical LLM orchestration and prompt engineering (LangChain or comparable), including agent/tool design, system-prompt and persona design, and guardrails.”
The ad says“Practical LLM orchestration and prompt engineering (LangChain or comparable), including agent/tool design, system-prompt and persona design, and guardrails.”
The ad says“Proven, hands-on depth with modern AI: you’ve personally built and shipped at least one production LLM/AI application. We know the LLM tooling is only a few years old — what you’ve actually built matters far more to us than years on a résumé.”
The ad says“Solid AWS experience (compute, storage, databases, containers, monitoring); familiarity with managed model services (e.g. Amazon Bedrock) and/or self-hosted model inference is a plus.”
The ad says“Practical LLM orchestration and prompt engineering (LangChain or comparable), including agent/tool design, system-prompt and persona design, and guardrails.”
The ad says“Strong Python and solid backend fundamentals (APIs, databases, data pipelines), with enough frontend ability to work end-to-end across the stack.”
The ad says“Strong experience building retrieval-augmented (RAG) systems — embeddings, vector databases, semantic search, and re-ranking — with a real feel for what makes retrieval accurate and dependable.”
The ad says“Strong experience building retrieval-augmented (RAG) systems — embeddings, vector databases, semantic search, and re-ranking — with a real feel for what makes retrieval accurate and dependable.”
The ad says“Strong experience building retrieval-augmented (RAG) systems — embeddings, vector databases, semantic search, and re-ranking — with a real feel for what makes retrieval accurate and dependable.”
The ad says“Solid AWS experience (compute, storage, databases, containers, monitoring); familiarity with managed model services (e.g. Amazon Bedrock) and/or self-hosted model inference is a plus.”
The ad says“Practical LLM orchestration and prompt engineering (LangChain or comparable), including agent/tool design, system-prompt and persona design, and guardrails.”
The ad says“Strong experience building retrieval-augmented (RAG) systems — embeddings, vector databases, semantic search, and re-ranking — with a real feel for what makes retrieval accurate and dependable.”

Full-Stack AI Engineer

Location: Remote (India-based) — Bengaluru preferred; with meaningful daily overlap with our UK and US teams

Engagement Type: Full-time — permanent, ongoing

About MarcoPolo Learning
MarcoPolo Learning is a leading provider of innovative content, technology, and instructional support for early childhood education. Since 2013, we’ve impacted thousands of classrooms and hundreds of thousands of families across North America. Our Emmy-nominated MarcoPolo World School app and The Polos TV series bring STEM and global discovery to life for young learners.

Backed by top-tier investors, we’re on a mission to transform early learning at scale. At the center of that mission is Audrey, our AI Teaching Companion & Coach — a guided AI assistant that helps early-learning educators plan lessons, discover the right materials, and improve classroom outcomes. We’re looking for a Full-Stack AI Engineer to help bring Audrey to life and shape where she goes next.

Role Overview

This is a role for an engineer who loves working where AI meets product. You’ll own the intelligence behind Audrey — the retrieval, generation, and logic that make her genuinely useful to teachers — while being just as comfortable moving across the backend and frontend to bring the whole experience together. You’ll work alongside our backend, infrastructure, and frontend engineers, with real ownership of the AI and real influence over what we build.

Audrey is approaching an exciting launch, and you’ll play a central part in shaping her — refining how she works today and helping define where she goes as we grow into more classrooms.

Just as much as the engineering, we care about instinct for the product. We’re looking for someone genuinely curious about the teachers we serve — an engineer who asks the right questions, understands how educators actually use what we build, and lets that understanding shape the experience. You’ll bring deep AI expertise, a natural instinct for collaboration, and a calm, considered approach to solving hard problems.

Key Responsibilities

Own the AI at the heart of Audrey — retrieval, generation, and the models and logic that make her intelligent and dependable.
Craft an experience where teachers instantly find exactly the right video, printable, or activity, with retrieval that’s fast, accurate, and reliable.
Build and refine the content and data pipelines that power Audrey — ingesting and structuring videos, printables, guides, and multilingual content for precise retrieval.
Work across the full stack, connecting the AI seamlessly into the wider product alongside our backend and frontend engineers.
Shape how Audrey thinks, responds, and guides teachers — designing her behavior, personality, and overall experience with the end user always in mind.
Help bring Audrey to launch and shape her evolution as we scale.
Continuously raise the quality, speed, and reliability of Audrey’s responses and recommendations.
Build fluently with modern AI-assisted development tools to design, build, and iterate quickly.
Partner with our infrastructure lead to keep Audrey running smoothly and efficiently in the cloud.
Put in place the evaluation, testing, and monitoring that keep quality high, and keep technical documentation clear.
Collaborate closely and openly with engineering and product, sharing your thinking and progress early and often.
Help shape the product roadmap — from deeper personalization to multilingual support and classroom insights.
Build with privacy and safety in mind, including FERPA/COPPA alignment.

What We’re Looking For

5+ years of software engineering experience across the full stack, comfortable working fluidly between backend and frontend.
Proven, hands-on depth with modern AI: you’ve personally built and shipped at least one production LLM/AI application. We know the LLM tooling is only a few years old — what you’ve actually built matters far more to us than years on a résumé.
Strong experience building retrieval-augmented (RAG) systems — embeddings, vector databases, semantic search, and re-ranking — with a real feel for what makes retrieval accurate and dependable.
An AI-native engineer who builds fluently with modern AI-assisted development tools (e.g. Cursor) and weaves AI through their workflow.
Strong Python and solid backend fundamentals (APIs, databases, data pipelines), with enough frontend ability to work end-to-end across the stack.
Practical LLM orchestration and prompt engineering (LangChain or comparable), including agent/tool design, system-prompt and persona design, and guardrails.
Solid AWS experience (compute, storage, databases, containers, monitoring); familiarity with managed model services (e.g. Amazon Bedrock) and/or self-hosted model inference is a plus.
A genuine product sensibility — you’re curious about the people who use what you build, and you let that shape your work.
A natural collaborator who communicates openly, builds trust across teams, and brings a calm, considered approach to a fast-moving environment.
Comfortable owning your work and driving it forward with minimal oversight.
Able to work remotely with meaningful overlap across UK and US time zones, with strong written communication.
Bonus: edtech or early-childhood education experience; multilingual retrieval; video/audio ML; familiarity with FERPA/COPPA or similar.

What We Offer

Competitive, market-aligned salary for an experienced engineer in India.
Fully remote, full-time role with flexibility over how you structure your day.
End-to-end ownership of the AI behind a flagship product, from launch through scale, with real influence over its architecture and roadmap.
A collaborative, family-friendly, mission-driven environment at the intersection of education, media, and technology.

Why Join Us

This is a rare chance to own the AI capabilities of a growing global education company at a defining moment. You’ll be the engineer who brings Audrey to life, shapes how she’s built, and helps take her from launch to a product used in thousands of classrooms. If you want work that’s visible, technically meaningful, and genuinely impactful for young learners and their teachers, this is it.

Note: This is an India-based engagement. Applicants must have the right to work in India; visa sponsorship is not available at this time.

MarcoPolo Learning is an Equal Opportunity Employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. We pride ourselves on a supportive and mission-driven working environment.

Asks for

Values