Interested in this AI/ML Engineer role at Hajoca Corporation?
Apply Now →About This Role
Hajoca Corporation is one of the country’s largest privately\-held wholesale distributors of plumbing, heating \& cooling, and industrial supplies. Founded in 1858, Hajoca is a company based on the principles of “Service, Integrity, Reliability,” and on relationships of trust and support with teammates, customers, and suppliers. Throughout its history, Hajoca has played an active role in shaping advances in plumbing. However, we attribute our success to two simple truths; a unique business philosophy and talented people. Hajoca is all about the people, who give us our advantage, and who will guide us successfully into the future.
Hajoca has over 400 locations nationwide, called Profit Centers; and at the foundation of our family of businesses is a National Support Center (NSC) where Centers of Excellence are dedicated to enabling the success of our Profit Centers.
The Information Security team in our National Support Center (NSC) is looking for an AI Enablement Lead at their Lafayette Hill, PA office. This is a hybrid role, requiring three days in office.
Are you a technology professional with a passion for artificial intelligence? Do you enjoy combining analytical thinking with strategic vision? Are you excited by the opportunity to lead and enable the use of AI across an entire organization? If so, then we’d like you to join our dedicated team as AI Enablement Lead.
About the Role:
The AI Enablement Lead leads the development and execution of AI enablement across Hajoca by establishing guardrails, policies, and scalable processes that support responsible AI adoption. Partnering with business and technology leaders across the organization, the AI Enablement Lead evaluates AI tools and use cases while translating emerging technologies into clear, practical guidance. They are responsible for driving organization\-wide awareness, training, and the sustained adoption of AI\-enabled workflows while ensuring alignment across stakeholders to balance innovation with risk.
In this role, you will:
Build the Program
- Help shape and execute Hajoca’s strategy for enabling responsible AI adoption across the business.
- Establish and maintain practical guardrails — policies, review processes, intake flows, and training — that allow the business to move quickly with AI while managing risk appropriately.
- Define what “good” looks like for AI usage at Hajoca and continuously evolve that definition as capabilities and the regulatory landscape change.
- Document repeatable patterns, standards, and playbooks that improve the consistency and scalability of AI enablement across departments.
- Define and track measures of success — adoption rates, usage trends, tool performance, and emerging risk signals — and present findings to the Sr. Manager and senior stakeholders to drive accountability and inform decisions.
Evaluate Use Cases \& Establish Partnerships
- Partner with business and technology leaders to evaluate proposed AI tools and use cases, identifying both opportunities and risks.
- Serve as a trusted advisor to leaders considering AI investments — helping them frame problems, evaluate vendors, and structure pilots responsibly.
- Translate prioritized use cases into implementation\-ready materials: workflow definitions, process considerations, requirements, and clear acceptance criteria that implementation teams can act on.
- Maintain visibility into AI activity across the company so the function can identify common patterns, scaling opportunities, and emerging risks.
Educate, Enable \& Adopt Change
- Develop and deliver AI awareness and training content for teammates at all levels — frontline, branch leadership, NSC, and executive audiences. Partner with the Learning Center team and Marketing \& Communications to develop and distribute content that lands effectively at scale.
- Lead targeted change adoption efforts in partnership with profit center leadership to drive effective, sustained use of AI\-enabled workflows — not just initial rollout, but lasting behavior change.
- Build a clear, accessible knowledge base of AI guidance, FAQs, and approved tools that teammates can rely on.
- Stay current on AI capabilities, regulatory developments, and industry practices, and translate them into clear, practical guidance.
Partner Cross\-Functionally on Risk \& Vendors
- Partner closely with the Manager, Cyber Security to ensure AI enablement and cyber security remain aligned on shared risks — data handling, third\-party tools, and identity.
- Partner with Procurement, Legal, and Information Security to oversee vendor relationships and contractual considerations for AI tools in use at Hajoca. Assess security, privacy, and compliance implications for new tools and ensure appropriate safeguards are in place prior to deployment.
- Escalate vendor service issues and coordinate remediation with internal stakeholders as needed.
- Coordinate with Legal, HR, and Procurement on AI\-related contracting, policy, and acceptable use questions.
- Partner with the Sr. Manager and Finance to maintain visibility into AI tool licensing and spend — tracking allocation across business units and ensuring the portfolio remains within budget parameters.
- Partner with Middleware Engineering and the Data \& Analytics team to ensure AI use cases access data through governed, well\-understood pathways — aligning on integration patterns, data source of record, access controls, and appropriate use of enterprise data in AI\-enabled workflows.
- Successfully complete required safety and compliance training programs as assigned.
- Perform other reasonably related duties as assigned by immediate supervisor and other management as requested.
About You:
- Bachelor's or Master’s degree in Computer Science, Data Science, Information Systems, Business, or a related field preferred.
- 5 or more years of progressive experience in technology, technology risk, governance, consulting, product management, or a related field — with meaningful exposure to AI or emerging technology adoption.
- Direct experience working with generative AI tools, AI platforms, or AI governance frameworks (e.g., NIST AI RMF, ISO/IEC 42001\) preferred.
Our ideal candidate will also:
- Have a demonstrated ability to translate emerging technology concepts into clear business guidance for non\-technical audiences.
- Have experience working across business and technology stakeholders to develop practical policies, processes, or programs.
- Have experience leading or supporting technology adoption initiatives, with an ability to drive sustained behavior change — not just launch and move on.
- Demonstrate strong written and verbal communication skills, with the ability to write for executives, frontline teammates, and everyone in between.
- Possess sound judgment, a builder’s mindset, and comfort operating in a function that is still being defined.
- Have experience producing structured implementation materials — workflow designs, process documentation, requirements, or playbooks — in support of technology programs.
- Have a background in cyber security, IT risk, privacy, or compliance, in addition to AI.
- Have experience with vendor evaluation, risk assessment, or technology contracting in an enterprise environment.
- Be able to provide leadership through influence by establishing credibility, building strong relationships, facilitating collaboration, and driving results across cross\-functional teams without direct supervisory authority.
- Have experience in a multi\-site or distributed business environment (distribution, retail, manufacturing, or similar).
- Possess strong interpersonal skills to build relationships and lead discussions.
- Demonstrate leadership qualities—innovation, decision making, mentoring, and influencing others.
- Be able to work effectively in cross functional teams and adapt to changing requirements.
- Be a quick learner who can master new technologies and collaborate effectively.
- Be willing and able to travel, up to 15%
The benefits of working with us:
Our culture is well\-suited for exceptional people who use their talents to drive business and want to share in the financial success their efforts yield. In addition to a competitive starting wage, we offer a Profit\-Sharing Program that provides each team member with an opportunity to earn a direct share of the profits on an annual basis. In addition to our generous compensation package, Hajoca also offers:
Full\-time benefits (for team members working 30 or more hours per week):
- Medical, dental, vision, and prescription coverage
- Accident, Hospital Indemnity, and critical care coverage
- Life insurance and Long Term Disability
- Pre\-tax accounts for healthcare, dependent care, and commuter benefits
- Paid vacation, holidays, and sick time (sick time also offered to PT team members as required by state law)
- Paid pregnancy and parental leave
- Paid day of community service
Full\-time and part\-time benefits:
- 401(k)
- Retirement cash account with company contributions
- Targeted training programs focused on your personal and professional growth
- Company wellness program
- Employee discounts
- College tuition benefits
- Please note that benefit offerings may differ for teammates employed through an intern program.
EEOC Statement
Hajoca Corporation is an Equal Opportunity Employer (Equal Opportunity Employer/Veterans/Disabled).
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity/expression, national origin, age, veteran status, disability, or any other protected category pursuant to federal, state or local laws and will not be discriminated against on the basis of any such categories/status. Hajoca is committed to providing reasonable accommodations for qualified individuals with disabilities including, but not limited to, during the application process. Please let us know if you need assistance or an accommodation due to a disability.
Background Screening Statement
We are a drug free workplace. Employment is contingent upon pre\-employment drug screening, and successful completion of a criminal background investigation subject to any federal, state and local laws.
Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 3,708 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At Hajoca Corporation, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills in Demand for This Role
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $218,750 based on 3,817 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $230,000.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
Hajoca Corporation AI Hiring
Hajoca Corporation has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Whitemarsh, PA, US.
Location Context
Across all AI roles, 14% (508 positions) offer remote work, while 3,180 require on-site attendance. Top AI hiring metros: New York (1,045 roles, $220,000 median); San Francisco (810 roles, $277,088 median); Los Angeles (397 roles, $215,000 median).
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (102) are outnumbered by mid-level (1,705) and senior (1,469) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $300,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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