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About This Role
Job Summary
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King County Housing Authority (KCHA) is actively seeking a Power Platform and AI Solutions Engineer (Senior Applications Developer) in our Tukwila, Washington\-based Information Technology department. The Information Technology department consists of three work groups: (1\) Infrastructure and Cybersecurity, (2\) Applications and Innovation, and (3\) Enterprise Solutions and Project Delivery. This position is part of Applications and Innovation, reporting to the Assistant Vice President of Applications and Innovation.
As a solutions engineer, you will bring Power Apps, Power Automate, Dataverse, CoPilot Studio, and Power BI expertise and act as a technical leader and mentor. You will translate business problems into low\-code/no\-code solutions built on the Power Platform.
We’re looking for a disrupter willing to break the business status quo and take our AI customer story to the next horizon: King County Housing Authority supports staff and residents with Microsoft 365 Copilot \| Microsoft Customer Stories
If you’re a rule breaker looking to innovate, you’ve come to the right place.
King County Housing Authority (KCHA), an independent municipal organization is a high performing nationally recognized leader in affordable housing. To learn more about KCHA and our Mission visit this link.
*We transform lives through housing.*
Essential Functions
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The Power Platform and AI Solutions Engineer (Senior Applications Developer) will have key responsibility for the following:
- Design, develop, configure, and maintain Power Platform solutions, including Canvas Apps, Model\-Driven Apps, Power Pages, Dataverse, Power Automate workflows, and related Microsoft technologies, using configuration\-first and low\-code development principles.
- Develop, deploy, and maintain AI solutions using Microsoft Azure AI Services and Microsoft Copilot Studio, and related Microsoft technologies.
- Design AI agents, copilots, automations, and integrations that improve business processes and increase employee productivity.
- Design and manage Dataverse environments, data models, security roles, business rules, integrations, and solution components to ensure scalability, maintainability, compliance, and governance.
- Govern application lifecycle management (ALM) processes, including source control, solution management, deployment automation, environment strategy, testing, and release management.
- Identify, evaluate, design, and implement platform enhancements, integrations, automation opportunities, and process improvements that improve service delivery, operational efficiency, and user experience.
- Design and develop Power BI dashboards, reports, and analytics solutions to provide operational insights, key performance indicators, adoption metrics, and process improvement measurements.
- Collaborate with infrastructure, security, architecture, records management, and business teams to ensure solutions comply with data governance, accessibility, records retention, classification, privacy, and security requirements.
- Produce and maintain technical documentation, solution design documents, standard operating procedures, training materials, quick\-reference guides, and knowledge\-base content to support adoption and long\-term maintainability.
- Serve as a technical escalation point and mentor for IT staff, conducting architecture reviews, design reviews, code reviews, and technical coaching.
Qualifications and Competencies
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Required Qualifications:
- Bachelor's Degree AND
- Considerable experience (3\+ to 5 years) in the areas of the Microsoft 365 implementation, Power Platform (Power BI, Apps, Automate, Pages), and Teams implementation OR
- An equivalent combination of experience and education that provides the necessary knowledge, skills, and abilities to perform the essential functions of this position.
Required Knowledge, Skills and Abilities:* Proficient in applications development principles, techniques, and procedures for both business and technical systems.
- Demonstrates expertise in systems analysis and design principles and various development methodologies for efficient system operation and maintenance.
- Understands database design concepts and is familiar with standard programming languages, utilities, and SQL queries used in similar environments.
- Competent with standard software development tools and utilities.
- Experienced in designing and operating information systems for standard computer platforms and peripherals.
- Demonstrates proficiency in cultivating an inclusive work environment that values diversity, treats others with respect, and fosters cooperation.
- Possesses strong communication skills, both written and verbal, conveying clear and timely messages to internal and external stakeholders; proficient in preparing clear and concise program documentation, user procedures, and reports.
- Experienced in creating training documentation and conducting end\-user training sessions.
- Utilizes excellent time management skills to efficiently complete project responsibilities and programming assignments in accordance with quality standards.
- Adaptable to evolving business needs and work responsibilities, responding positively to change while embracing and incorporating new practices and values.
- Demonstrates the ability to work independently and as a team member, fostering effective working relationships; works cooperatively, exchanging ideas, and addressing issues in a constructive and collaborative manner.
- Exhibits analytical skills, using experience and perspective in problem\-solving and decision\-making; exercises independent judgment in communicating decisions or actions.
- Proficient in using MS Office applications, including Word, Excel, Outlook, and internet tools.
Special Requirements:* Final candidates may be required to complete a criminal background and motor vehicle record check in accordance with applicable law.
- Consent to and pass required assessments.
- Must possess a valid driver's license to travel to KCHA sites as required. Must have an acceptable driving record at time of appointment and throughout employment.
Position Information and Application Process
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Application Requirements:
To be considered for this opportunity, you must:
- Complete the online application profile in its entirety.
- Upload a cover letter that addresses how your experience and education qualifies you to perform the essential functions listed in the job announcement. (Cover Letter)
- Upload a detailed résumé of all educational and professional experience. (Résumé)
Salary \& Benefits:
The starting salary range for this position is $120,698\.88 \- $144,838\.65 annually dependent on qualifications and professional experience. The complete salary range for this position is $120,698\.88 \- $168,978\.43 annually. Performance based merit increase opportunities and Cost of Living Adjustments (COLA) are reviewed on an annual basis. A comprehensive health care benefits package for you and your dependents includes medical, dental and vision insurance, life and long\-term disability insurance plans, vacation, sick and personal leave, tuition reimbursement, and retirement benefits are also available. For more details regarding KCHA comprehensive benefits, please visit ourbenefits page.
Work Environment:
After initial onboarding, this position will have the opportunity to work remotely up to 100% in accordance with the KCHA's flexible work arrangements; however, remote work conditions will be reviewed on a regular basis based on business and program need. Employees must reside in Washington State and have the ability to report to the Central Office in Tukwila will be required. Some local and domestic travel may be required to support KCHA business needs.
Physical Requirements:
*Incumbent(s) must be able to meet the physical requirements of the classification and have mobility, balance, coordination, vision, hearing and dexterity levels appropriate to the functions performed. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.*
This work requires the frequent exertion of up to 10 pounds of force and occasional exertion of up to 25 pounds of force; work regularly requires sitting, using hands to finger, handle or feel and repetitive motions, frequently requires speaking or hearing and occasionally requires standing, walking, stooping, kneeling, crouching or crawling and reaching with hands and arms; work has standard vision requirements; vocal communication is required for expressing or exchanging ideas by means of the spoken word; hearing is required to perceive information at normal spoken word levels; work requires preparing and analyzing written or computer data, operating motor vehicles or equipment and observing general surroundings and activities; work has no exposure to environmental conditions; work is generally in a moderately noisy location (e.g. business office, light traffic).
Equal Opportunity:
King County Housing Authority is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or veteran status.
Salary Context
This $120K-$168K range is below the median for AI/ML Engineer roles in our dataset (median: $180K across 1841 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 3,708 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At King County Housing Authority, 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 $218,750 based on 3,817 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $230,000. This role's midpoint ($144K) sits 34% below the category median. Disclosed range: $120K to $168K.
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.
King County Housing Authority AI Hiring
King County Housing Authority has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Tukwila, WA, US. Compensation range: $168K - $168K.
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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