Training Consultant

At NIIT, we're transforming the way the world learns, for the better. That's why the world's best-run learning functions across 30 countries trust us with their learning and talent. Since 1981, we have helped leading companies transform their learning ecosystems while increasing the business value of learning. Our comprehensive, high-impact managed learning solutions weave together the best of learning theory, technology, operations, and services to enable a thriving workforce.

Link to our website - https://www.niit.com/en/learning-outsourcing/

Job details:

We are hiring a technically strong instructor to deliver a structured, hands on bootcamp on an Agentic AI Framework and its associated compliance and automation tooling. The program is delivered to cohorts that include Forward Deployed Engineers and a broader mix of technical practitioners, business analysts, and consulting professionals

Responsibilities:

Teaching and Content Delivery

• Deliver technical sessions across the multi day arc covering agentic AI system design, multi agent orchestration, runtime policy enforcement, and prototyping with AI tooling.

• Translate technically dense content into clear, accessible explanations for a diversely skilled audience spanning advanced engineers, intermediate practitioners, and career transitioning participants.

• Explain multi service architectures and end to end request flows clearly to engineering audiences. • Teach agentic AI concepts including agent loops, tool calling, task decomposition, DAG based orchestration, and retrieval augmented generation.

• Teach AI compliance concepts including policy as code principles, runtime guardrails, rule engines, and audit logging for regulated environments.

• Open and close each day with structured welcome and debrief routines and adapt depth and pacing in real time based on cohort ability distribution surfaced during introductions and labs.

Live Demonstrations and Lab Facilitation

• Run live technical demonstrations of agentic AI workflows.

• Ability to walk all lab exercises in parallel with participants on a shared screen, setting time expectations and announcing progress checkpoints.

• Monitor participant progress during labs, identify who is stuck, and intervene early with pairing or targeted support rather than waiting for a hand to be raised.

• Troubleshoot and fix common environment issues during preparation and delivery. Escalate unresolvable issues to the program lead or technical support without losing cohort momentum.

• Deliver a concise recap after each lab connecting its outcome to the next module.

Cohort Management

• Recognize and respond to different skill levels within the cohort. Proactively pair, redirect, or stretch participants based on their progress.

• Create a learning environment where participants feel safe asking questions, taking risks, and surfacing problems early.

• Ability to manage groups of 50 to 100 participants in virtual or hybrid settings or sets of ten participants in breakout rooms, while maintaining session energy and engagement across a full week of training.

• Circulate between breakout groups during lab and hackathon time, asking guiding coaching questions to keep teams focused and scoped.

Continuous Improvement

• Maintain a running log of environment issues, participant questions, and instructional friction encountered during delivery.

• Contribute observations and recommendations to the post cohort improvement process within 48 hours of delivery.

• Keep delivery materials current with the latest lab instructions and known issue workarounds before each cohort.

Strongly Recommended (Must Have) Technical Skills :

The instructor will debug participant environments live in front of the cohort. Fluency, not awareness, is required in the following areas:

• Linux: shell navigation, file and permission management, package installation, basic text editing.

• Bash scripting: variables, conditionals, loops, script execution, and troubleshooting.

• Python: data types, control flow, functions, modules, JSON handling, REST API calls. Comfortable reading and debugging asynchronous Python.

• Git: clone, branch, commit, push, pull requests, and merge conflict resolution.

• REST APIs: HTTP verbs, JSON request and response structure, token and API key authentication patterns. • Containerization: running containers, reading compose files, port mapping, inspecting logs, and basic container networking.

• LLM APIs: able to explain what an LLM API call is, why context windows matter, and how tool

NIIT is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other protected characteristic.