Talent Acquisition + AI
Joshua Lollman
Making AI work for recruiting.
Focused on prompts, workflows, and tools.
About
Joshua Lollman
Seven years in talent acquisition. Started as a recruiter, managed a recruiting team for several years, now lead AI adoption and operations infrastructure.
The recruiting background matters. I know what breaks in high-volume recruiting because I've lived it. Not as a consultant watching from the outside, but as the person trying to make the numbers work.
That experience shapes how I approach AI: I start with the actual problem, define what "good output" looks like in recruiting, then decide if AI helps. Most AI tools solve the wrong problem or create new ones.
I work on AI adoption, prompt design, and practical tools. The hard part isn't the technology. It's getting people to engage with it honestly and building systems that hold up in production, not just demos.
Background
Current focus and prior roles
Current (2024-Present)
Lead AI adoption and TA operations for a global Financial Services organization. Work with recruiting teams on ops infrastructure and process design.
I work on AI adoption for recruiting: prompts, training, workflow guidance, and usage tracking. When something moves to production, I work with engineering on requirements, edge cases, test scenarios, evaluation, and issue tracking. They build it; I make sure it fits real recruiter workflows.
Build prompt frameworks and evaluation methods for AI applications in recruiting. Define criteria, output standards, and validation.
Work with Legal, Cybersecurity, and HRIS on AI governance. Lead TA-wide compliance audits. Share findings with TA leadership quarterly.
Before (2021-2024)
Managed a recruiting team supporting high-volume hiring. Improved retention through process changes while maintaining quality and fill rate.
Built operational infrastructure—trackers, audit tools, knowledge libraries, process docs—that the team (and eventually others) used. Active member of process improvement efforts.
Earlier (2018-2021)
Before moving into leadership, I worked as a full-cycle recruiter from high-volume customer service roles through director-level searches. I was brought in to replace external support, stabilize hiring manager relationships, and expand coverage as the approach proved out.
I came from staffing—technical recruiting under MSP agreements, business development, and client management—where delivery commitments and SLAs weren't negotiable. That's where I learned how recruiting feels when you're responsible for both the numbers and the relationships.
What I Do
How I help recruiting teams use AI
AI rollout + training
Workshops, coaching, documentation. I show recruiters and leaders how to evaluate AI tools, use them, and understand risk. The hard part isn't the technology. It's getting people to engage with it honestly.
Prompt Engineering
Prompt templates for common recruiting tasks. The hard part isn't the syntax. It's knowing what good output looks like in recruiting and working backward from there.
Workflow Design
Map recruiting processes before automating them. It shows what's manual, what adds cognitive load, and what's actually broken. That tells you where AI fits and where it doesn't.
Automation & Tooling
Data cleanup, content generation, workflow utilities. I build these with AI-assisted development. I'm not a developer, but I know the problem well enough to spec it and test until it works.
AI Tool Partnership
I work with engineering on recruiting AI. I bring the recruiter perspective—pain points, test scenarios, output checks. They build it; I make sure it solves the right problem.
AI Compliance Awareness
Tracking US hiring AI legislation—CA, IL, NY, and what's emerging elsewhere. I'm not a lawyer, but someone needs to stay current and help the team understand the risks.
Selected Work
Work examples in practice
Real problems. Practical fixes.
AI Adoption Framework
The problem: Organizations introduce AI tools and see low usage. Recruiters don't know when or how to use them, and leaders struggle to assess impact or identify where support is needed.
What I built: Adoption framework—workflow guidance, prompt templates for common recruiting tasks, structured training, usage tracking, measurement approach. Built for distributed recruiting teams.
Approach: Start with recruiting pain points, not features. Build tools for real workflows, train on realistic scenarios, track adoption patterns. Account for local context—language, time zones, market differences.
Outcome: Consistent usage across distributed teams. Less rework from better tool fit and training. Framework model is expanding to other HR functions.
What made it work: Treat it as change management, not a feature release. The model is rarely the problem.
Compliance Audit Automation
The problem: Manual compliance reviews for recruiting content couldn't keep up with posting volume. Non-compliant postings reaching candidates, no visibility for leadership, reactive cleanup instead of proactive prevention.
What I built: Automated audit system—PowerShell extraction from ATS, JSON rules engine, HTML dashboard. Processes hundreds of requisitions, flags violations by category, generates correction guidance for recruiters, and gives leadership real-time compliance visibility.
Approach: Built it in one morning between meetings. Designed for easy handoff—documented setup process, no specialized technical knowledge required. Rules engine separated from code so non-technical partners can update compliance requirements.
Outcome: Saves 10+ hours weekly and eliminated manual spot-checking. Gave leadership real-time compliance data they didn't have. Audit trail for compliance documentation. Better input quality for downstream AI tools.
Lesson learned: Sometimes the best solution isn't elegant. It's the one you can ship same-day and maintain without a developer.
Approach
How I work
I'm not a developer, but I break problems down and use AI-assisted or low-code tools to build what teams need.
Complex projects go through engineering. I build smaller tools with AI-assisted workflows. Either way, it's recruiting problems solved by someone who's worked them firsthand.
Tools & references
Small, working outputs
Written for TA leaders, recruiters, and founders working with AI in hiring.
For recruiters: Prompt Console
For TA leaders / founders: Evaluation Rubric · Implementation Failure Modes
Small, working outputs. Tools and references I use when recruiters work with AI. No sales pitch needed.
Prompt Console
Build structured prompts with clear sections: task, context, constraints, output format. It cuts missed requirements and "reasonable but wrong" outputs.
Markdown basics
Minimal Markdown for structuring prompts for chat LLMs. Short on purpose. Focused on what improves instruction-following.
Generative AI vs Statistical AI in recruiting
Two different technologies, both called "AI." Understanding which type a tool uses changes how you evaluate outputs, risk, and workflow fit. Short reference to sanity-check vendor demos.
How I evaluate recruiting AI tools
A rubric for separating useful tools from demo theater. Covers workflow fit, output quality, auditability, and risk.
AI implementation in recruiting: what breaks in the real world
The failure modes that derail adoption: input quality, ownership, audit trail, adoption, drift. A practical look at AI in recruiting workflows.
Contact
Contact
Open to conversations in the space.