Technical Curriculum Developer - Gen AI

Nxtwave Disruptive Technologies; Hyderabad; On-site; INR 1,200,000 - 1,500,000; Full time

Job summary

Nxtwave Disruptive Technologies in Hyderabad seeks a Gen AI Curriculum and Systems Engineer to design and run agentic learning systems that generate and quality-check learner content. You will own the outcomes those systems produce and shape the learning programs that learners study.

You’ll build and maintain curriculum, modules, and assessments, create engaging content, and ensure content stays current and compliant with quality standards.

Qualifications

• 1–3 years building software or AI/automation systems with at least one deployed, evaluated agentic workflow or LLM-integrated app.
• SME-level GenAI knowledge: prompt design, RAG, vector databases, hosted LLM APIs.
• MERN + Python to build surfaces your agents plug into and write your own logic and integrations.
• Hands-on with an agent/automation framework (n8n, LangGraph, LangChain, CrewAI).
• An evaluation instinct: you design rubrics before trusting outputs and treat unmeasured agents as unfinished.
• Awareness of hallucination, prompt injection, latency, and cost at scale; guard against them.
• You use AI tools (Claude, Cursor, ChatGPT, Copilot) daily in building.
• You write clearly: precise, structured, easy to follow.

Responsibilities

• Design, develop, and maintain curriculum, learning modules, and assessments for Generative AI programs through Agentic Workflows.
• Create engaging learning content, including lesson plans, presentations, assignments, projects, coding exercises, and quizzes.
• Own the quality bar: design eval sets, rubrics, and guardrails that decide what's good enough to ship, and contribute content.
• Keep content accurate and current: fix outdated GenAI concepts, deprecated libraries, wrong syntax, or broken code within SLA.
• Contribute to curriculum R&D: experiment with new tools/frameworks, with at least one quarterly update or recommendation.
• Build foundations that keep the pipeline running: memory, knowledge bases, integrations, observability, and issue clearing.

Skills

GenAI concepts

Prompt design

RAG

Vector databases

Hosted LLM APIs

MERN stack

Python

LangChain

Agentic workflows

Tool-calling workflows

Multistep frameworks

Education

B.Tech / B.E. in CS or related

Tools

n8n

LangGraph

LangChain

CrewAI

GitHub

Job description

Gen AI Curriculum and Systems Engineer

Role overview:

This role sits where GenAI engineering meets learning content. You'll design and run the agentic systems that generate and quality-check what learners study, and you'll own the outcomes those systems produce, not just the code behind them. You will play a key role in designing, developing, and enhancing learning programs. This role is ideal for individuals who enjoy creating learning experiences, structuring educational content

What you'll own:

You'll build the AI systems that generate and quality-check our learning content (lesson scripts, coding exercises, graded projects, MCQs) and own that content through to what reaches learners. The agents are how the work gets done; what you're accountable for is content that ships quickly, holds up under assessment, and stays current.

• Design, develop, and maintain curriculum, learning modules, and assessments for Generative AI programs through Agentic Workflows
• Create engaging learning content, including lesson plans, presentations, assignments, projects, coding exercises, and quizzes.
• Own the quality bar: design the eval sets, rubrics, and guardrails that decide what's good enough to ship, and author enough content yourself to keep that judgment sharp.
• Keep content accurate and current: catch outdated Gen AI concepts, deprecated libraries, wrong syntax, or broken code examples within a week of discovery, and fix them within SLA.
• Contribute to curriculum R&D: experiment with new tools and frameworks, and proactively flag what's worth adding or retiring, with at least one R&D-driven update or recommendation each quarter.
• Build the foundations that keep the pipeline running and improving on its own: memory, knowledge bases, integrations, observability, and clearing the issues that stall generation or loading.

How we'll measure it:

Content:

velocity (more shipped per cycle), efficiency (lower cost and effort per unit), effectiveness (learners who complete it pass what they're assessed on), and relevancy (it stays current).

Business:

skill-assessment success percentage, a minimal delta between content and assessment, and more learners landing in the ideal engagement bands.

Must-have

• 1 - 3 years building software or AI/automation systems, with at least one deployed, evaluated agentic workflow or LLM-integrated app you can show us (GitHub or live demo, not a tutorial follow-along).
• SME-level working knowledge of GenAI (prompt design, RAG, vector databases, hosted LLM APIs), plus the content ability to judge, produce, and correct technically accurate learning material.
• MERN + Python, enough to build the surfaces your agents plug into and write your own logic and integrations.
• Hands-on with an agent/automation framework (n8n, LangGraph, LangChain, CrewAI, or equivalent), including multi-step, tool-calling workflows.
• An evaluation instinct: you build the rubric before you trust the output, and treat an unmeasured agent as unfinished.
• A feel for where things break, from hallucination and prompt injection to cost at scale and latency, and how to guard against it.
• You use AI tools (Claude, Cursor, ChatGPT, Copilot) as a real part of how you build, every day.
• You write clearly: precise, structured, easy to follow.

Nice-to-have

• EdTech, assessment, or structured-content experience.
• Observability and eval tooling (LangSmith, RAGAS, or similar), and CI/CD for content pipelines.
• A public trail of how you learn: a thoughtful README, a walkthrough, a blog post, an open-source contribution.

Why this role

GenAI content is being figured out as it's built, and this is a seat where you help shape how it's done rather than execute someone else's playbook. You'll own real systems, see their impact on real learners, and have the room to experiment, ship, and improve fast. If you've built something you're proud of and you're hungry to build more, we'd love to see it.

Location:

Hyderabad (In-office)

Workweek:

5 days

Employment type:

Full-time