Tech Talent Acquisition

Here's 16 common hiring mistakes ranked by how hard they are to solve: EASY FIXES 1. Copy-paste job posts Still using that job description from 2015? The one that says "must be a team player" and "5+ years experience required"? You're filtering out incredible talent who assume you're another boring company. 2. Slow response time Taking 2 weeks to email candidates back? They've already accepted another offer. The best people have options. 3. No interview prep Watched too many interviewers walk in cold and ask "so tell me about yourself" for 45 minutes. Create a simple question bank. Train your team. 4. Unclear next steps "We'll be in touch" is where good candidates go to die. Tell them exactly what happens next. Basic respect that most companies miss. STANDARD PROBLEMS 5. Wrong interviewers Your backend engineer interviewing salespeople because "they were free"? Stop it. Match interviewers to roles. Train them on what to look for. Bad interviewers drive away good candidates. 6. No scorecard One person loves them because they're "smart." Another hates them because they're "too aggressive." Meanwhile you have no idea what actually matters for success. Build scorecards before you interview anyone. 7. Poor selling Interviews are two-way. You're so busy evaluating them, you forget to explain why they should drop everything to join your vision. Sell that vision. 8. Bad timing Three month interview processes for a senior role? They're gone. Match process to seniority. Move fast on junior roles. Go deep on senior ones. DEEP ISSUES 9. No success metrics "We need someone good" isn't a hiring strategy. What does success look like in 30/60/90 days? What metrics matter? If you can't define winning, you can't hire winners. 10. Bias in process Hiring people because they went to Stanford or remind you of yourself? You're building a monoculture that will fail. 11. Zero feedback That amazing candidate who didn't quite make it? They'll trash you on Glassdoor if you ghost them. Or they'll improve and be perfect next year if you give them real feedback. Most companies choose ghosting. 12. Pipeline neglect Only recruiting when someone quits is like only eating when you're starving. Build relationships before you need them. CRITICAL PROBLEMS 13. Role design failure Badly designed roles attract desperate people, not talented ones. Period. 14. Unrealistic expectations Want someone with 10 years experience, startup hustle, and enterprise polish? Cool. That person makes $500K at Google. You're offering $120K and some options. Math doesn't work. 15. Toxic culture You can hire all the A-players you want. If your culture sucks, they'll leave in 6 months. Then you're back to hiring, except now you have a reputation. Fix the culture or stop wasting everyone's time. 16. No hiring strategy Making it up as you go works until it doesn't. Usually around 20 people when everything breaks. What else would you add? 👇

Demand for software engineers is as bad now as it was during the peak of the pandemic. In 18 months, the number of data engineering job openings on LinkedIn has been cut in half. It’s not the end of technical roles, but the data shows demand is changing. Trying to replace engineers with low-code tools and #AI code generators fails. However, most platforms now support technical and nontechnical co-development environments. A new type of technical role has gained traction in businesses. Smaller software and data teams build frameworks and tools for nontechnical developers on a co-development platform that’s available to anyone in the business. Meta and JPMC implemented enterprise-wide co-development platforms and are seeing massive benefits. One or two technical resources are embedded into the nontechnical team to support their development efforts. Solutions are developed faster and more closely meet customer and business needs because domain experts build them. A few advanced R&D teams still operate in the business but focus on building larger, more innovative products. Teams supporting incremental features and internal operations initiatives are going away. While demand is falling in some areas, it’s rising for the embedded, business-facing technical roles. There are three levels: 1️⃣ Domain Expert Technical ICs: Value-centric #data engineers, data analysts, and software engineers who support nontechnical developers and are embedded into their organizations. 2️⃣ Product Manager Engineers: Technical capabilities with deep product strategy expertise. They know what to build and can implement high-value features independently or with a team. 3️⃣ Technical Strategists: Technical experts who work with executive and C-level leaders. They bring data, models, and rapid product development capabilities to the strategy planning and implementation processes. I have taught data and AI strategy, #ProductManagement, and value-centric capabilities to technical ICs for 8 years to meet today's demand shift. Technical roles are evolving, and amazing opportunities exist for people who adapt.

Hello to those hiring generative AI engineers and generative AI architects. Your job descriptions are all over the place, you need to define them properly. The roles of a generative AI engineer and a generative AI architect, while interconnected, focus on different aspects of working with generative AI systems. Here's a breakdown of their primary differences: ### Generative AI Engineer **Role and Responsibilities:** 1. **Development and Implementation:** - Writing and testing code for generative models (like GPT, GANs, etc.). - Implementing algorithms and neural network architectures. - Fine-tuning pre-trained generative models to achieve desired outputs. - Programming in languages such as Python, and using frameworks like TensorFlow, PyTorch, etc. 2. **Experimentation:** - Conducting experiments to improve model performance. - Monitoring the training process and making necessary adjustments. 3. **Data Handling:** - Preparing and processing data for model training. - Handling datasets, including data cleaning and augmentation. 4. **Quality Assurance:** - Testing models to ensure they generate high-quality, relevant content. - Debugging and troubleshooting model issues. ### Generative AI Architect **Role and Responsibilities:** 1. **System Design:** - Designing the overall architecture of generative AI systems, ensuring they meet business and technical requirements. - Deciding on the integration of various components (data pipelines, model deployment frameworks, user interface). 2. **Strategic Planning:** - Defining the roadmap and selecting the appropriate technologies and tools for generative AI projects. - Making high-level decisions about model selection, system requirements, and scalability. 3. **Coordination and Leadership:** - Coordinating with stakeholders (product managers, data scientists, engineers) to ensure the design aligns with user needs and business goals. - Leading and mentoring engineering teams. 4. **Optimization and Performance:** - Ensuring that the system architecture supports efficient model training and inference. - Implementing measures for scalability, maintainability, and security. 5. **Innovation:** - Keeping abreast of the latest advancements in generative AI and integrating new techniques and methodologies where appropriate. - Proposing new ideas and solutions that leverage generative AI for business value. ### Summary - **Generative AI Engineers** are more hands-on with the coding, model training, and testing aspects. They focus on the practical development, fine-tuning, and implementation of generative models. - **Generative AI Architects** are involved in the high-level design, strategic planning, and system integration aspects. They focus on the broader system architecture, ensuring that the generative AI system fits within the organizational infrastructure and meets overall goals.

Streamline Your New Hire Journey with SAP SuccessFactors Onboarding SAP SuccessFactors Onboarding is more than just an orientation tool—it's a pivotal solution that connects seamlessly with other modules to ensure new hires feel supported from day one. Here's how it integrates with key modules: 👉 Recruiting: Automatically transition candidates into the onboarding process directly from their application. 👉 Employee Central: Facilitate smooth conversion of candidates into employees, whether or not they're sourced via Recruiting. 👉 Learning: Assign courses to new hires even before their first day, ensuring they hit the ground running. 👉 Performance & Goals: Empower employees by setting goals as part of their onboarding journey with templates for New Hire Goal Management. 👉 DocuSign: Enable digital signatures for forms, ensuring compliance and ease across devices. 👉 Qualtrics Employee Lifecycle: Collect actionable feedback through automated surveys triggered upon program completion. Opportunities for Enhanced Integrations: There are potential areas to amplify the onboarding experience: 👉 ITSM tools like ServiceNow: Automate provisioning of equipment and systems access for new employees. What integrations do you think are essential for a next-gen onboarding process? Share your thoughts below! 👇 #SAPSuccessFactors #Onboarding #HRTech #EmployeeExperience #Integration

“We’ll hire when we need someone.” 🤦🏻♀️ I'm sorry, that’s not a Talent Acquisition strategy. That’s a reaction. And reacting too late is one of the most expensive mistakes a business can make. If you want to grow sustainably, hire top talent and stay competitive, you need a Talent Acquisition strategy that’s not just a hiring plan, but a business lever. So, what does that actually include? Here are 5 core pillars every company should consider: 1️⃣ Workforce planning: → What roles will you need in 6–12–18 months? → Where are the skill gaps? → How do your hiring needs align with business growth? 2️⃣ Employer Branding and Candidate Experience (CX): → Do the right people know who you are and why they should work for you? → What do candidates say about their experience with you, especially the rejected ones? 3️⃣ Sourcing Strategy: → Are you relying only on inbound? → Do you know where your ideal candidates actually are and how to reach them? 4️⃣ Diversity, Equity & Inclusion: → Are your job descriptions, processes and interview panels inclusive? → Are you building teams with different perspectives and backgrounds? 5️⃣ Recruiting Infrastructure & Data: → Do you measure time-to-hire, conversion rates or quality of hire? → Is your TA team set up with the right tools, training and headcount to support growth? Because here’s the thing: If you don’t invest in TA strategy early, you'll eventually struggle with: 🚨 Delayed product launches 🚨 Burned out teams 🚨 Rising attrition 🚨 Missed revenue targets 🚨 Damaged reputation in the market Talent Acquisition is not a support function. It’s not just about posting jobs and scheduling interviews. It's a strategic function that belongs at the same table as product, finance, and operations. Because without the right people, none of those other strategies can succeed.

Recruiters are expected to evolve into strategic business partners, playing a crucial role in aligning talent acquisition with overall business goals. Transformation is happening Automation and AI are handling routine tasks like resume screening and interview scheduling, allowing recruiters to focus on strategic initiatives1. This shift enables them to spend more time understanding business needs and crafting effective talent strategies. Recruiters are immersing themselves in their clients' industries, understanding market dynamics, operational challenges, and competitive landscapes. This knowledge helps them anticipate the skills and competencies needed for future success. Using data analytics, recruiters are making informed decisions about workforce planning and talent management. This approach ensures that recruitment strategies are aligned with business objectives and market trends. The human element remains irreplaceable. Recruiters are prioritizing empathy and communication, building authentic relationships with both clients and candidates. This helps in matching not just skills but also cultural fit. Recruiters are transitioning from tactical roles to strategic problem-solvers. They are designing unique candidate experiences, crafting compelling employer value propositions, and developing innovative sourcing strategies. Continuous learning and upskilling are essential. Recruiters are enhancing their skills to stay ahead of industry changes and to provide strategic insights to their organizations. This evolution positions recruiters as valuable assets, driving business success through strategic talent acquisition.

In IT recruiting, I’ve seen this more times than I can count. A hiring manager says: ❌ “The candidate rate is too high.” ❌ “We already have this profile from different vendor.” ❌ “No feedback. or Sudden New Update” ❌ “We’ll keep the resume for different role .” Many recruiters stop there. They see the rejection… and move on. But the real opportunity? It’s beneath the surface. Instead of negotiating blindly or just “checking back later,” change the approach: ✔ Ask what skill gaps the current team is struggling with ✔ Understand the business impact of the role staying open ✔ Identify what the current vendor isn’t delivering ✔ Reframe the conversation from rate to ROI (time-to-fill, quality, retention, project delay cost) Now let’s talk about the other side — candidate challenges. Because sometimes the issue isn’t budget. It’s market reality. In today’s IT hiring market: ❌ Niche tech stacks have a limited talent pool ❌ Strong candidates have 3–4 offers in hand ❌ Candidates reject onsite/hybrid roles ❌ Visa constraints shrink the available pool ❌ Long interview cycles cause offer drop-offs ❌ Unrealistic rate vs. skill expectations create mismatch If we don’t address these realities upfront, we waste weeks sourcing profiles that won’t convert. So instead of just “finding candidates,” shift the conversation: ✔ Calibrate must-have vs. good-to-have skills ✔ Align budget with market rates ✔ Shorten interview turnaround ✔ Sell the opportunity, not just screen resumes ✔ Position the role competitively against other offers Same goal: closing the position. Different approach: solving the hiring challenge on both sides. In IT recruiting, the real value isn’t in sending 10 resumes. It’s in aligning business expectations with market reality. Dig deeper. That’s where the real placements happen. 🚀 #ITRecruiting #TechRecruiter #TalentAcquisition #StaffingLife #HiringChallenges #RecruitmentStrategy

I recently had a debate with a few people outside the HR space who believed that recruitment is simple—just pick people to work, right? But anyone who has been involved in hiring knows it’s far more complex. Recruitment isn’t just about filling seats; it’s about shaping the future of an organization. The process requires strategic thinking, foresight, and balance. To illustrate this, I introduced The Three Core Challenges in Recruitment: 1. The Skills vs. Potential Dilemma Many companies hire for experience, but in a rapidly evolving world, adaptability and learning ability often outweigh a long resume. Do we hire for what someone knows or for what they can become? 2. Culture Fit vs. Culture Add Hiring people who align with company culture can create harmony, but too much similarity can lead to stagnation. Instead of just looking for a “fit,” we should seek those who challenge the status quo and bring fresh perspectives. 3. Speed vs. Precision In today’s competitive market, speed is crucial. A great candidate won’t wait for months-long processes. But rushing recruitment often leads to poor hires. How do we balance urgency with thoroughness? Recruitment is both an art and a science, and mastering it means navigating these challenges effectively. Curious to hear your thoughts—what’s the biggest hiring challenge you’ve faced? #RecruitmentChallenges #HiringStrategy #TalentAcquisition #FutureOfWork #HRLeadership

Cloud Infrastructure Engineers, System Administrators, and Site Reliability Engineers (SREs) all deal with IT systems and infrastructure, they focus on different aspects of operations, scalability, and reliability. 🔧 1. System Administrator (SysAdmin) Focus: Maintaining and managing on-premise or cloud-based servers, systems, and networks. Key Responsibilities: Install, configure, and maintain servers and OS. Monitor system performance and troubleshoot issues. Manage backups, patches, and user permissions. Usually reactive and operational (responding to issues as they arise). Tools: Linux/Windows servers, Active Directory, Bash/Powershell, Nagios, Puppet/Chef (sometimes). ☁️ 2. Cloud Infrastructure Engineer Focus: Building and maintaining scalable cloud environments (AWS, Azure, GCP). Key Responsibilities: Design and deploy cloud-based architectures. Manage cloud services like EC2, VPCs, Load Balancers, Kubernetes. Handle networking, security, storage, and compute resources in the cloud. Often involved in DevOps automation and IaC (Infrastructure as Code). Tools: Terraform, CloudFormation, Kubernetes, Docker, AWS CLI, Azure DevOps, GCP Console. ⚙️ 3. Site Reliability Engineer (SRE) Focus: Ensuring systems are reliable, scalable, and automated—bridging software development and operations. Key Responsibilities: Write code to automate infrastructure and operations. Define SLAs, SLOs, and SLIs for system reliability. Monitor availability and performance proactively. Perform incident response and root cause analysis. Strong DevOps mindset: reliability as a software engineering problem. Tools: Prometheus, Grafana, PagerDuty, Ansible, Go/Python, Kubernetes, CI/CD pipelines.

Your hiring process sounds good in theory…but falls apart in real life. Here are 3 steps to fix it: Most hiring teams design for an ideal world. Unlimited bandwidth Predictable candidate engagement Evenly spaced job openings That world doesn’t exist....especially now. HR is juggling five other things Candidate decisions are out of your control Roles open when they open Before we fix it, let’s align on what actually matters: Hear from enough qualified candidates to make a sound hiring decision for the organization. That’s the goal (phrasing aside). The breakdown happens because most teams rush to design their hiring process. They build around “best practices” without factoring in their real capacity. And, two things usually occur: A) The process looks great on paper, but can’t be executed consistently. Follow-through slips Communication slows Resentment builds across HR, hiring managers, and candidates. or B) They know they’re stretched thin, so they avoid improving anything at all. They default to the status quo because “we don’t have time to change this.” Neither outcome is about effort. It’s about order. Here’s the order that works: Step 1: Become capacity aware Acknowledge the real constraints you have so you set your hiring process up for success. It's about assessing what cracks or conditions have caused hiring to go awry in the past. Examples: increased applicant volume, interview coordination, hiring manager accountability Step 2: Design structure within those constraints Build a process that protects what matters most (getting to know your candidates) while being able to overcome capacity challenges. Examples: agree to a max number of interviews, assign clear ownership to each step of the process Step 3: Reinforce the structure with tools Use tools as leverage to accomplish what you've designed in step 2 while also creating capacity which can be reinvested into better communication and decisions. Examples: asynchronous candidate screening, automated interview scheduling, task assignment in your ATS Most teams skip Step 1. And when they do, everything downstream feels harder than it should. Good hiring starts with your ability to execute. Don't set yourself up for failure by ignoring reality. (Sharing a simple visual below that walks through this)