Your Job Descriptions Are Broken AF!

Let’s be real – the world’s biggest companies are still churning out trash job descriptions for their digital and IT roles, and it's time to call them out.

My colleague, Neil Jumalon and I have spent the past few months digging through open “IT” positions across big-name enterprises.

We’ve found an avalanche of broken, jargon-filled, anti-inclusive postings that scream, “This isn’t for you!”

From demanding pointless years of experience to requiring irrelevant degrees and a laundry list of certifications, these descriptions are bloated with keywords, outdated, and fail miserably at telling you what the job is. They completely miss the mark on what hiring for digital talent should look like today. ??

Who’s Doing It? A Lot of Big Names – But We Won’t Name and Shame

We’re not here to name and shame because almost every company and government out there is guilty.

From Fortune 500 giants to public sector dinosaurs, they’re all pumping out rigid job descriptions loaded with buzzwords and meaningless credentials, completely missing the point: finding people with the right skills.

And yeah, maybe we don’t want to make enemies out of potential clients – but this isn't about finger-pointing. It's about fixing the mess: crafting skills-focused job descriptions that attract the talent you need without pushing people away. ???

The Impact of AI, Automation, and Robotics

Why does this matter right now? Because AI, automation, and robotics are flipping the workforce upside down, traditional job descriptions aren’t keeping up. Roles are evolving at lightning speed, and digital skills are changing overnight.

SFIA (Skills Framework for the Information Age) isn’t just another buzzword—it’s a tool for?determining exactly what skills are needed for roles in a world where technology is constantly reinventing itself.

SFIA and the SFIA Foundation are cutting through the noise by giving us a common language for defining and measuring skills—whether for humans, AI, or automated systems. It lets you compare quantifiable human skills side-by-side with what emerging tech can do, helping organizations understand how to effectively hire, upskill, and deploy people, AI, and automation.

Example 1: Broken Job Description (Traditional Approach)

Title: IT Operations Manager

Job Description: We seek a dynamic, experienced IT Operations Manager to join our rapidly growing team. The ideal candidate will be a self-starter, capable of driving multiple priorities simultaneously and ensuring alignment with cross-functional teams to maintain operational excellence. This role will require 10+ years of relevant IT experience, a master’s degree in computer science or related fields, and a deep understanding of ITIL, COBIT, and Six Sigma methodologies.

Key Responsibilities:

• Oversee all IT operations, ensuring all systems are always functioning optimally.
• Develop and enforce standard operating procedures (SOPs) to maintain maximum uptime and service continuity.
• Coordinate with internal and external stakeholders to drive best-in-class operational performance.
• Ensure compliance with industry standards and company policies through rigorous auditing and documentation.
• Lead a team of IT professionals to ensure adherence to KPIs, SLAs, OLAs, and overall departmental targets.
• Continuously monitor industry trends to ensure our IT infrastructure aligns with our strategic business goals. Qualifications:
• A Master’s degree in computer science, Information Systems, or a related field is required.
• A minimum of 10 years of progressively responsible IT experience.
• Mandatory ITIL v4 Expert certification.
• Lean Six Sigma Black Belt preferred.
• Strong background in network operations, server management, and database administration.
• Proven track record of cross-functional leadership.
• Excellent communication and presentation skills.

SFIA-Optimized Job Description

Title: IT Service Operations Lead

Overview: The IT Service Operations Lead ensures optimal IT service delivery and drives continuous improvement. This role requires familiarity with tools like ServiceNow, Jira, and Splunk, but equivalent experience with similar platforms is equally valued.

Required SFIA Skills and Levels with Applications:

1. Service Level Management (SLMO - Level 5/6) Competency: Develop and monitor SLAs using ServiceNow to set performance targets, track system uptime, and monitor incident response times.
2. Problem Management (PBMG - Level 4/5) Competency: Conduct root cause analysis, document resolution processes, and implement preventive actions for recurring IT issues using the ServiceNow Problem Management Module.
3. Change Control (CHMG - Level 5/6) Competency: Lead the change control process through Jira, performing risk assessments and ensuring proper documentation and tracking of changes.
4. Configuration Management (CFMG - Level 4/5) Proficiency: Maintain and update the ServiceNow CMDB, ensuring accurate documentation of all IT infrastructure components.
5. Methods and Tools (METL- Level 4/5) Competency: Provide specialized expertise in Microsoft Azure and VMware, implementing enhancements and troubleshooting performance issues to align with organizational needs.

What’s Different?

Let’s break it down: the traditional job description is bloated with fluff. “Master’s degree required,” “10+ years of experience,” “ITIL v4 Expert certification” – it’s the same old laundry list that tells you nothing about the actual work. It’s all about stacking up buzzwords and arbitrary requirements without a single clear idea of what you’ll actually be doing day-to-day.

But look at the SFIA-optimized version – it’s a complete 180. Instead of vague qualifications, it lays out exactly what the IT Service Operations Lead is expected to achieve. Forget about endless degrees and certifications – the focus is on real, actionable skills: Service Level Management using ServiceNow, Problem Management through root cause analysis, Change Control via Jira, and technical expertise in Azure and VMware.

It’s about getting down to the nitty-gritty of the job – what tools you’ll use, the challenges you’ll face, and how you'll drive impact.

It’s all measurable, it’s all practical, and it’s clear as day what success looks like. No more guessing. No more fluff. Just a straightforward, skills-focused breakdown of precisely what the job requires.

Example 2: Program Manager – DevSecOps

Broken Job Description (Traditional Approach)

Title: Program Manager – DevSecOps

Job Description: Are you passionate about bridging Development, Security, and Operations? As a Program Manager – DevSecOps, you will lead large-scale programs to enhance our organization's DevSecOps initiatives. You must be an exemplary leader with 15+ years of experience and a stack of certifications like PMP, ScrumMaster, CISSP, and DevSecOps Practitioner.

Key Responsibilities:

• Lead and manage the DevSecOps program, ensuring adherence to timelines, budgets, and quality benchmarks.
• Establish frameworks, guidelines, and policies for development, security, and operations.
• Spearhead Agile transformation initiatives, working with cross-functional teams to implement CI/CD practices.
• Oversee software development lifecycle metrics and performance measurements. Qualifications:
• A bachelor’s degree in computer engineering or a related discipline is required; an MBA is preferred.
• Mandatory certifications: PMP, ScrumMaster, CISSP, DevSecOps Practitioner.
• A minimum of 15 years of relevant experience in large-scale enterprise environments.
• Strong background in software engineering, cybersecurity, and cloud orchestration.

SFIA-Optimized Job Description

Title: DevSecOps Transformation Manager

Overview: The DevSecOps Transformation Manager leads secure and efficient software delivery, integrating development, security, and operations. Proficiency with tools like GitLab, Azure DevOps, and SonarQube is expected, but equivalent experience with CI/CD and security platforms is also valued.

Required SFIA Skills and Levels with Applications:

1. Systems Development Management (DLMG - Level 5/6) Competency: Manage build and deployment pipelines through GitLab and Jenkins, ensuring code quality via continuous integration.
2. Systems and Software Life Cycle Engineering (SLEN - Level 4/5) Competency: Integrate secure coding standards into the development lifecycle using SonarQube and Snyk for security scanning.
3. Continuity Management (COPL - Level 4/5) Competency: Maintain automated CI/CD pipelines in Azure DevOps, integrating testing and deployment for optimal delivery.
4. Stakeholder Relationship Management (RLMT - Level 5/6) Competency: Collaborate with developers, security teams, and product owners using tools like Confluence to align goals and priorities.
5. Change Control (CHMG - Level 4/5) Competency: Apply change management methodologies, facilitating adoption of DevSecOps practices across the organization.

What’s Different?

The traditional job description for the Program Manager – DevSecOps is a never-ending wish list of credentials, years of experience, and buzzword-filled responsibilities. It’s obsessed with “must-haves” like 15+ years in the field and a pile of certifications – PMP, ScrumMaster, CISSP – but ultimately fails to get to the heart of the role. It’s all about jumping through hoops and ticking boxes instead of focusing on the actual skills and value that a DevSecOps pro brings to the table.

The SFIA-optimized version? It’s like ripping the Band-Aid off. Straight-up skills, no fluff. It tells you precisely what you’ll do: manage build pipelines, secure code from start to finish, run CI/CD like a pro, work together with development and security teams, and actually make change happen. It cuts the crap and gives a breakdown of real expectations, the tools you’ll need, and how you’ll make an impact.

No more confusing qualifications. No more jumping through impossible hoops. Just a clear path to know if you’ve got what it takes to own the role.

Example 3: Data Scientist

Broken Job Description (Traditional Approach)

Title: Data Scientist

Job Description: We seek a results-oriented Data Scientist who can dive deep into complex datasets and drive data-informed decision-making. The ideal candidate will have 8+ years of experience in data analysis, machine learning, and statistical modeling. A Ph.D. in Statistics, Mathematics, or Data Science is required.

Key Responsibilities:

• Analyze large datasets and design predictive models.
• Lead the development of ETL processes and data pipelines.
• Establish KPIs and build dashboards and visualizations.

Qualifications:

• A Ph.D. in a relevant field is mandatory.
• Minimum of 8 years in data science, analytics, or related field.
• Proficiency in Python, R, SQL, Hadoop, Spark, and TensorFlow.

SFIA-Optimized Job Description

Title: Data Science & Analytics Specialist

Overview: The Data Science and Analytics Specialist extracts actionable insights from data to inform business decisions. Experience with tools like Python, Power BI, and Tableau is preferred, but proficiency with similar data analysis, visualization, and modeling tools is equally valued.

Required SFIA Skills and Levels with Applications:

1. Data Science (DATS - Level 5/6) Competency: Perform complex data wrangling using Python libraries like Pandas and NumPy to clean, transform, and analyze datasets.
2. Machine Learning (MLNG - Level 5/6) Competency: Develop predictive models and machine learning algorithms using scikit-learn and TensorFlow, applying statistical techniques to forecast outcomes and derive insights.
3. Database Design (DBDS - Level 4/5) Proficiency: Design and manage data storage solutions in PostgreSQL or MongoDB, optimizing for data retrieval and analysis efficiency.
4. Data Visualization (VISL - Level 4/5) Competency: Create interactive dashboards and compelling visualizations in Power BI and Tableau that present complex data to stakeholders in an understandable format.
5. Programming/Software Development (PROG - Level 4/5) Proficiency: Develop scripts in R and Python to automate data processing, analysis, and model development, using GitHub for version control.

What’s Different?

The traditional job description for the Data Scientist is like throwing up roadblocks at every turn – 8+ years of experience and a mandatory Ph.D. for what? The responsibilities are so vague that you’re left wondering if you’re applying for a research position, a coding boot camp, or a unicorn-wrangling job. Proficiency in Python, R, SQL, Hadoop, Spark, and TensorFlow – all of them? Great, but how do you expect a candidate to juggle every one of those tools daily? There’s no clarity, no real-world context – just a never-ending list of qualifications designed to narrow the talent pool to absurdity.

Now, the SFIA-optimized version doesn’t play those games. It’s straight-up about the skills you need and how they’ll be used. Data Analysis? You’re wrangling data with Python libraries like Pandas and NumPy. Machine Learning? You’re building models with scikit-learn and TensorFlow – no mystery, just real applications. And forget about forcing you down one educational pathway; it’s all about the skills and the practical experience you bring to the table.

You know exactly what tools you need, how they’ll be used, and why they matter for the business.

There are no ridiculous barriers,?no guessing games,?just a clear, skills-based breakdown that says, “If you can do the work, you’re what we’re looking for.”

The SFIA Advantage: A Better Way Forward

Traditional job descriptions? Yeah, they're broken. Compliance-driven, outdated, and stuck in the mud. They throw in rigid degree requirements, random years of experience, and a list of responsibilities that don’t even get close to what the actual job is. Here’s why they’re failing:

1. Exclusionary Language: Obsessing over degrees and certifications shuts out tons of qualified, diverse talent. It's a filter, not a door opener.
2. Keyword Overload: Packed with empty buzzwords and fluff, these descriptions lack clarity on what the role actually means.
3. Can’t Keep Up: They’re all about what you’ve done before, not what you’re capable of—missing the mark entirely in tech roles that evolve faster than these descriptions do.

SFIA’s Approach Fixes That By:

• Prioritizing Skills Over Titles: Forget job titles and years spent on the clock. It’s about what you know and what you can actually do. Period.
• Clarity and Inclusion: Competencies are clearly defined, cutting out the jargon. It’s an open invite for talent from all backgrounds, not just those who tick every box.
• Adaptability to Emerging Tech: SFIA isn’t stuck in the past. It keeps pace with emerging tech, letting you stay relevant in a world that’s changing every minute.

It’s Time to Fix What’s Broken!

Stop using the same stale job descriptions if you want to attract the right digital talent.

Transform them. SFIA-based descriptions shift the focus to what matters—skills.

They give hiring managers and applicants a clear, straightforward view that attracts the right talent while being inclusive and transparent.

Let’s be real—your job descriptions are broken AF. But now you know exactly where they went off the rails and how to start fixing them.

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