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About This Role
Development
Position Type
Full Time
Location
Nashville, TN, United States
Job ID
FUNDR002933
Nashville, Tennessee, United States
Position Summary:
As Vice President, Development, you will put your proven sales and relationship management skills to work driving success and achieving revenue goals through positive engagement with staff and community volunteer leaders.
Utilizing your proven networking skills, you will identify and cultivate relationships with key community leaders and C-Suite corporate partners effectively. As a recognized leader and fundraiser in the peer-to-peer space, you will coach and inspire your team to build successful event growth strategies through community and volunteer engagement.
In this key chapter leadership position, you will work closely with Chapter and cross-functional leadership developing ambitious, comprehensive development strategies and goals that align with the Association’s strategic plan and deliver measurable results. You will contribute your professional fundraising leadership experience in leading, coaching and mentoring your team of professional development staff.
This position is based in Nashville, TN, covering the state of Tennessee.
Responsibilities
This role is right for you if;
- You are an enthusiastic and active member of the community, utilizing your engaging networking skills to build sustainable corporate and community partnerships to achieve organizational revenue goals
- You have a vision for building a comprehensive development strategy that produces aggressive revenue growth
- You are able to drive success and provide positive engagement with staff and volunteers through coaching, recognition, and mutual accountability
- You have successfully recruited, managed, and coached fundraising staff and volunteers to effectively implement best and proven practices to achieve fundraising goals with a priority on Walk to End Alzheimer’s
- You are known as a uniter and have successfully built a positive, healthy, and inclusive team environment
- Your experience in providing inspirational leadership, oversight and implementation of fundraising programs has resulted in meeting or exceeding revenue goals around mass market events/special events, corporate sponsorship and other corporate gifts, pipeline development for major and planned gifts and other areas of development
Qualifications
What you Bring:
- Bachelor’s degree preferred in sales/business or related field. CFRE is a plus but not required.
- 7+ years proven leadership experience in peer-to-peer, fundraising, and other diversified fundraising programs. Experience with mass market events like Walk is required
Knowledge, Skills and Abilities
- Ability to effectively analyze and utilize data to increase productivity and enhance results
- Has a strong track record for networking and cultivating key C-Suite community and corporate leaders
- Proven success in bringing community and corporate leaders to the table to fulfill volunteer leadership roles
- Experience in strategic implementation planning, budget development and management
- Successful experience in supervising, coaching and motivating fundraising staff and volunteers
- Capable of working cross-functionally to build capacity
- Excellent written and verbal communications skills
- Attention to detail and solid project management skills
- Proficiency with applications for Microsoft Office (Excel, Word and PowerPoint), Google Suite (Docs, Sheets, Slides), and teleconferencing software, such as Zoom
- Proficiency with Internet and database/fundraising applications, preferably Luminate
- Ability and willingness to work a flexible schedule, including evenings, early morning and occasional weekends
- Willingness and ability to represent the Chapter at meetings and special events
- Ability to travel extensively in chapter territory, as well as occasional overnight travel
- Valid driver’s license, proof of vehicle insurance and access to reliable, personal vehicle to meet travel requirements
Title: Vice President, Development
Position Location: Nashville, TN
Full time
Position Grade & Compensation: Grade 211 *The Alzheimer's Association’s good faith expectation for the salary range for this role is between $110,000 - $145,000.*
*This position is eligible for a $15,000 sign on bonus.*
There is a performance based incentive opportunity up to $13,000, depending on portfolio size and achievement of quarterly goals.
Reports To: Chapter Executive
Who We Are:
The Alzheimer’s Association is the leading voluntary health organization in Alzheimer’s care, support and research. Our mission is to lead the way to end Alzheimer's and all other dementia– by accelerating global research, driving risk reduction and early detection, and maximizing quality care and support.
The Alzheimer’s Association announced a landmark $100 million investment in research for 2023. This unparalleled commitment is illustrative of the momentum we are building in dementia research — our investments today will lead to breakthroughs tomorrow.
At the Alzheimer’s Association, our employees are at the core of all we do. Our network of more than 1,750 employees across the United States makes a difference each and every day for those impacted by Alzheimer’s and those at risk for the disease.
We warmly invite qualified applicants to consider this opportunity to make a life-changing impact on the millions living with Alzheimer’s, their caregivers and those that may develop the disease in the future. Read on to learn more about the role, then visit our website www.alz.org/jobs to explore who we are and why we've been recognized as a Best Place to Work for the last twelve years in a row.
At the Alzheimer's Association®, we believe that diverse perspectives are critical to achieving health equity — meaning that all communities have a fair and just opportunity for early diagnosis and access to risk reduction and quality care. The Association is committed to engaging underrepresented and underserved communities and responding with resources and education to address the disproportionate impact of Alzheimer’s and dementia.
The Alzheimer’s Association commitment remains steadfast in engaging all communities in our full mission. The Association provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment to the fullest extent required by law, including, but not limited to, on the basis of race, color, religion, age, sex, national origin, gender identity, disability status, genetics, protected veteran status, sexual orientation, or any other legally protected characteristic.
Employees working 24 hours/week or more are eligible for a comprehensive benefits package, including medical, dental, vision, flex accounts, short and long-term disability, life insurance, long term care insurance, tuition reimbursement, generous Paid Time Off, 12 annual holidays and Paid Family Leave, as well as an annual Cultural & Heritage Day and Volunteer Day of their choosing. They are also eligible for our gold standard 401(k) retirement plan.
Full time employees (37.5 hours/week), will enjoy all of the above plus an annual School Visitation Day and an Elder Care Facility Day of their choosing.
Salary Context
This $110K-$145K range is below the median for AI/ML Engineer roles in our dataset (median: $170K across 217 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 37,339 AI roles we're tracking, AI/ML Engineer positions make up 91% of the market. At Alzheimer's Association, 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 $154,000 based on 8,743 positions with disclosed compensation. This role's midpoint ($127K) sits 17% below the category median. Disclosed range: $110K to $145K.
Across all AI roles, the market median is $190,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $300,688. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Safety ($274,200). By seniority level: Entry: $85,000; Mid: $147,000; Senior: $225,000; Director: $230,600; VP: $248,357.
Alzheimer's Association AI Hiring
Alzheimer's Association has 5 open AI roles right now. They're hiring across AI/ML Engineer. Positions span Houston, TX, US, St. Louis, MO, US, Nashville, TN, US. Compensation range: $81K - $180K.
Location Context
Across all AI roles, 7% (2,732 positions) offer remote work, while 34,484 require on-site attendance. Top AI hiring metros: New York (1,633 roles, $204,100 median); Los Angeles (1,356 roles, $179,440 median); San Francisco (1,230 roles, $240,000 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 37,339 open positions tracked in our dataset. By seniority: 3,672 entry-level, 23,272 mid-level, 7,048 senior, and 3,347 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (2,732 positions). The remaining 34,484 roles require on-site or hybrid attendance.
The market median for AI roles is $190,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $300,688. Highest-paying categories: AI Engineering Manager ($293,500 median, 21 roles); AI Safety ($274,200 median, 24 roles); Research Engineer ($260,000 median, 264 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 37,339 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (33,926), AI Software Engineer (823), AI Product Manager (805). 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 (3,672) are outnumbered by mid-level (23,272) and senior (7,048) 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 3,347 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 7% of all AI roles (2,732 positions), with 34,484 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 $190,000. Top-quartile roles start at $244,000, and the 90th percentile reaches $300,688. 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 $293,500 median, while Prompt Engineer roles sit at $145,600. 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: Rag (23,721 postings), Aws (12,486 postings), Rust (10,785 postings), Python (5,564 postings), Azure (3,616 postings), Gcp (3,032 postings), Prompt Engineering (2,112 postings), Kubernetes (1,713 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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