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About This Role
### The Role
The AI Senior Consultant is a billable, customer\-facing consultant who designs and delivers AI and intelligent automation solutions on the Microsoft stack, with Business Central at the core. You will help our customers connect Microsoft Copilot (and adjacent assistants such as Claude) to Business Central, build in\-product agents using Microsoft’s Copilot Studio agent toolkit, and ship Power Automate solutions that turn AI from a buzzword into measurable business outcomes.
You will also operationalize our internal AI use by running Western Computer as Customer Zero, so we build, prove, and refine these patterns on ourselves before we sell them to customers.
This is a working\-manager role with no direct reports today. You will serve as a subject\-matter expert and capability\-builder for the broader practice (BC, F\&SCM, CE), not the only person in the company doing AI work. The job is to make everyone else better at it. You will report to the VP of AI Transformation.
### What You’ll Do
- Lead customer\-facing AI and intelligent automation engagements, including discovery, scoping, solution design, and delivery of Copilot Studio agents, Power Automate flows, and AI Builder solutions for Microsoft Business Central customers, with F\&SCM and CE adjacencies.
- Design and build in\-product agents using Microsoft’s Copilot Studio agent toolkit, including connecting Microsoft Copilot and Claude to Business Central data and workflows.
- Build intelligent automation across business processes using Power Automate cloud and desktop flows, AI Builder for document and form intelligence, and Dataverse\-backed solutions that reduce manual effort and accelerate delivery.
- Support Sales and Pre\-Sales on AI\-related customer requests, including demos, discovery workshops, scoping calls, and SOW input.
- Operationalize Western Computer’s AI go\-to\-market by helping to productize, package, and launch the AI and automation service offerings on our 2026 roadmap.
- Run Western Computer as Customer Zero by building internal agents and automations that improve our own delivery, support, and operations. The internal work becomes the reference architecture for the customer work.
- Champion AI and automation adoption across the BC, F\&SCM, and CE practices through enablement, training, and reusable templates.
- Stay current on Microsoft’s Agentic AI roadmap (certifications, product releases, and partner motions) and translate that into what Western Computer should do next.
### Must\-Have Qualifications
- Hands\-on consulting experience with Microsoft Dynamics 365 Business Central, including functional implementation experience and comfort reading and modifying AL extensions.
- Demonstrable, shipped work in Copilot Studio, Power Automate, and AI Builder, such as copilots, agents, cloud and desktop flows, or AI Builder document and form models that real users use today. We will ask for examples.
- Hands\-on Power Platform fluency across Power Apps (canvas and model\-driven), Power Automate, Dataverse, and AI Builder.
- Customer\-facing consulting fluency across discovery, workshops, demos, and SOW input. You can credibly stand in front of a customer and design a solution.
- Self\-directed delivery. You can take a vague problem and turn it into a scoped, shipped agent or automation without being micromanaged.
- US\-based and authorized to work in the US.
### Nice\-to\-Have Qualifications
- Experience with Dynamics 365 Finance \& Supply Chain Management or Customer Engagement (CE/CRM).
- Active progress on the Microsoft Agentic AI certification path, such as AB\-730 (AI Business Professional), AI\-901 (Azure AI Fundamentals), AB\-900 (Copilot \& Agent Admin Fundamentals), AB\-620 (AI Agent Builder Associate), Copilot Studio Academy, AB\-410, AI\-103, or AB\-100\.
- RPA experience with Power Automate Desktop for legacy system automation.
- Familiarity with non\-Microsoft assistants (Claude, ChatGPT, OpenAI) and how they integrate with Microsoft business applications.
- Experience packaging consulting services, including building offerings, scoping templates, and repeatable IP.
- Background in one of Western Computer’s focus verticals: wine, food \& beverage, manufacturing, distribution, or home builders.
### About You
This role is for builders, not pontificators. We are looking for someone who pairs Microsoft business\-applications fluency with hands\-on AI and automation delivery.
We are not hiring a pure data scientist or ML researcher. The market and our customer base are not there yet. We are also not hiring an AI enthusiast who cannot show what they have shipped, or a Microsoft Business Applications consultant who has not actually used Copilot Studio, Power Automate, or AI Builder in delivery.
If you have stood up agents, flows, or Copilot extensions that real people use, and you can also do that inside a Business Central context, this is the role.
### Why This Matters Now
Western Computer is committing to AI and intelligent automation as the next leg of our business, both inside the company and as services we deliver to customers. This is the first dedicated hire in that effort. The person who takes this role will not be one of many AI consultants. They will be the one who proves the model works, builds the playbook the rest of the practice follows, and helps Western Computer earn the right to be our customers’ AI and automation partner of choice.
### The Perks:
- Stellar Salary: Get ready to be rewarded handsomely, with a competitive salary ranging from $140k \- $160k USD per year. Your skills and experience are pure gold, and we want to show you the appreciation you deserve.
- Super Healthcare Benefits: Say goodbye to worries about medical, dental, and vision costs. We've got your back with access comprehensive healthcare coverage, and yours is covered!
- Retirement Treasure: Invest in your future with access to a 401(k)\-retirement plan. Your financial security is important, and we're here to help you build it.
- Time to Chill: We believe in the power of relaxation. Enjoy generous paid time off for vacations, holidays, and those inevitable sick days. Work hard, but don't forget to play hard!
- Remote Work Magic:Embrace the freedom to work remotely from the location of your choice.
### Who we are:
We've been on an exciting mission since 1987 to partner with customers as they transform and grow their businesses. As a Microsoft Solution Partner, we’re recognized as a top partner. We owe that success to our team of 150\+ Microsoft Dynamics 365 and Power Platform solutions experts who pair business needs with system capabilities to create the recipe for success. We are continuously innovating to maximize our customers’ technology investments. From our IP products to our teams who always have a little fun, we are not your average ERP company.
*We encourage you to apply even if you feel that you do not meet all of the above qualifications. Frequently cited statistics show that women and underrepresented groups are more likely to only apply to jobs if they meet 100% of the listed qualifications. Western Computer encourages you to break that statistic and to apply. No one ever meets 100% of the requirements. We look forward to your application!*
Salary Context
This $140K-$170K range is below the median for AI/ML Engineer roles in our dataset (median: $180K across 1937 roles with salary data).
View full AI/ML Engineer salary data →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 3,823 AI roles we're tracking, AI/ML Engineer positions make up 69% of the market. At Western Computer, 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 Required
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 $181,170 based on 12,692 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($155K) sits 14% below the category median. Disclosed range: $140K to $170K.
Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and AI Safety ($274,200). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $247,800; VP: $250,000.
Western Computer AI Hiring
Western Computer has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Oxnard, CA, US. Compensation range: $170K - $170K.
Location Context
Across all AI roles, 15% (590 positions) offer remote work, while 3,217 require on-site attendance. Top AI hiring metros: New York (2,643 roles, $211,000 median); San Francisco (2,168 roles, $253,000 median); Los Angeles (1,792 roles, $191,580 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 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.
The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 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 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). 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 (112) are outnumbered by mid-level (1,798) and senior (1,516) 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 397 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 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 $200,100. Top-quartile roles start at $253,500, and the 90th percentile reaches $307,500. 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 Engineering Manager roles lead at $275,000 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 (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 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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