Learning and Development Lead, Agentic AI Upskilling Program

We are building a high-impact upskilling program to turn experienced machine learning engineers and commercial builders into Forward Deployed Engineers (FDEs) capable of delivering agentic AI solutions to clients. This is not a traditional L&D role. You will own the entire program design, content strategy, and execution from day one, moving fast and building operational rigor as you scale.

The FDE upskilling program is built on a proven framework: competency mapping, byte-sized daily learning (20 minutes a day, not weeks of courses), practical gates that verify skill through working builds, and cohort-based learning with leaderboards. Your job is to operationalise this framework, source or build content, commission external practitioners where needed, and deliver certified FDEs into the field within six weeks per cohort.

This role requires someone who can move between strategy (designing the learning architecture) and execution (sourcing a Udemy clip, writing a recipe, coordinating with a practitioner), who is comfortable with ambiguity and incomplete information, and who can rally engineering leaders and line managers to make the program work.

Key Responsibilities

Content Curation and Sourcing

• Own the end-to-end content pipeline: decide what to curate (40%), what to build (35%), and what to commission (25%).
• Curate best-in-class content from Udemy, industry platforms, and open-source libraries; clip and sequence material to exact competencies.
• Build recipe-style playbooks and step-by-step guides using NotebookLM, Claude, and other tools, tailored to our stack and client scenarios.
• Commission external FDE practitioners to record on-screen coding walkthroughs and hands-on demonstrations; manage quality and turnaround.
• Manage content lifecycle: track versioning, flag stale units, push quarterly update packets without full rebuilds.

Program Design and Delivery

• Partner with engineering leadership to map competencies: decompose current skills into focus areas, define observable can-dos, and set mastery bars.
• Design the daily 20-minute learning experience: structure the Watch (curated clip) / Do (hands-on sandbox work) / Prove (assessment) pattern.
• Build the four-gate system: entry diagnostic (Codeira), unit checkpoints (auto-graded), competency gates (practitioner panel), and FDE certification (demo day).
• Operate the LMS and learning platform: configure Codeira for personalised sequencing, wire sandbox environments, connect to Workday for tracking and Slack for leaderboards.
• Plan and run cohorts: schedule daily drips, manage practitioner assessors, coordinate demo days, and iterate based on data and feedback.

Vendor and Tool Management

• Identify and procure the LMS platform; negotiate terms and manage implementation.
• Establish relationships with external FDE practitioners; brief them on scenarios, manage recording schedules, QA output.
• Own integrations with Codeira (AI-assisted tutoring), NotebookLM (content generation), Workday (reporting), and any other tools in the stack.

Stakeholder Alignment

• Work with engineering leadership to secure assessment panel capacity, scenario input, and feedback on certified FDEs.
• Engage line managers: help them nominate engineers for cohorts, communicate expectations, and track live-work application of skills.
• Communicate progress to executives: provide monthly scorecards on gate pass rates, time-to-competency, certified FDE headcount, and revenue impact.

Program Scaling

• Build operational playbooks and checklists so the program can be run repeatably for multiple cohorts without you personally executing every step.
• Document the nine-step runbook (decompose, set bar, source units, produce micro-units, wire LMS, drip, gate, apply, refresh) so that scaling becomes mechanical.
• Identify capacity bottlenecks early: assessment panel, practitioner availability, LMS limits, content production pace.

What You'll Bring

Core Strengths

• 5-7 years in L&D, instructional design, or curriculum development, ideally in technical domains (engineering, data science, software development).
• Proven ability to own a learning program end to end: from design through execution through iteration. You've built content, managed projects, and handled ambiguity.
• Comfort with moving between strategy and tactics. You can write a content sourcing rubric, then spend a morning clipping a Udemy video. Both matter.
• Strong project management discipline: you track dependencies, manage timelines, and communicate status clearly. You know when something is 80% and good enough, and when it needs another pass.

Technical and Platform Literacy

• Hands-on fluency with LMS platforms (we are still choosing, but you should understand SCORM, xAPI, user provisioning, reporting).
• Familiarity with AI-assisted tools: you have used Claude, ChatGPT, NotebookLM, or similar to brainstorm, draft, or refine content.
• Ability to learn new tools quickly. Codeira, Workday, Slack integrations, sandbox environments: you will pick up the specifics as we go.

Domain Knowledge

• Deep familiarity with machine learning, agentic AI, or related technical domains. You don't need to code, but you need to understand concepts like tool calling, RAG, orchestration, guardrails, and evaluation well enough to vet content quality.
• Experience building or evaluating training for MLEs, data scientists, or software engineers. You understand what hands-on, scenario-based learning looks like in technical domains.

Soft Skills

• Communication: you can explain a learning design to an engineer, a sponsor to a founder, and a blocker to a practitioner without ambiguity.
• Resilience: you will hit no's, broken links, practitioners who ghost, and cohorts that under-deliver. You stay calm and find a workaround.
• Intellectual humility: you are willing to change your mind based on data (gate pass rates, feedback, attrition) and learner outcomes, not sunk cost in content you built.

Mindset

• Bias toward action: you will have incomplete information. You ship with what you have, measure the result, and iterate.
• Product thinking: you see this as a learning product, not a course. You obsess over completion, engagement, and outcome (certified skill applied on live work), not enrolment or hours watched.
• Startup mentality: you are comfortable with tight budgets, scrappy tools, and doing work that would normally be split across three roles. You figure out how to get leverage.

What This Role Is Not

• This is not a training coordinator role. You will not be scheduling Zoom calls full time or managing rosters.
• This is not a solo subject matter expert role. You will partner with engineers and practitioners, but you are the orchestrator, not the source of all knowledge.
• This is not a curriculum design-only role. You own end-to-end delivery, which means sitting in practitioner recordings, pushing content into the LMS, and troubleshooting leaderboard bugs.

Compensation and Benefits

• Competitive salary based on experience and market rates for L&D leadership roles in tech.
• Standard company benefits: health insurance, retirement plan, flexible work arrangements.
• Learning budget: we will fund your access to platforms, courses, or certifications that keep you sharp.
• Impact: your work will directly influence how we upskill engineering talent and expand our FDE delivery capacity.

How to Apply

Submit your resume, a cover letter explaining why this role excites you, and answers to these two questions:

1. Tell us about a time you owned an end-to-end learning program or project from design to delivery. What was the biggest challenge, and how did you solve it?
2. Describe a technical topic you have learned deeply or taught. How would you approach making it accessible to someone with a different background or skill level?

You can send your application to campusdelivery@quantiphi.com.