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About This Role
About Us
Orr Group is a strategic partner to nonprofit organizations, helping them solve some of the world's most pressing challenges. Through our embedded partnership model, we go beyond traditional consulting - providing hands-on leadership, expertise, and execution to drive transformative fundraising and organizational growth. For over 30 years, we have collaborated with mission-driven organizations to design and implement innovative fundraising strategies, grow revenue, and build capacity to ensure long-term success. Our work spans campaign management, major gifts strategy, board development, planned giving, talent management, and beyond. We remain nimble, forward-thinking, and results-driven, helping our clients navigate an ever-evolving philanthropic landscape.
Position Summary
Orr Group is seeking a Senior Associate Director, AI & Development Operations to help lead and deliver client engagements across AI strategy, workflow automation, and implementation projects. The ideal candidate has worked inside nonprofit development and operations teams, knows fundraising best practices, and can look at a client's systems and processes and see what's working, what's broken, and what's possible. They pair that judgment with hands-on technical skill and can build and deploy the automations, integrations, and AI tools they recommend.
Senior Associate Directors serve as core members of client project teams, managing day-to-day execution in partnership with the Director, who sets project direction and serves as the primary point of contact. They work directly with nonprofit executives, development and fundraising teams, operations leaders, and technology stakeholders, and may lead less complex engagements on their own.
Responsibilities
Each project at Orr Group is specially tailored and designed for the needs of that particular client. Generally, Senior Associate Directors manage day-to-day project execution, lead the development of deliverables, and carry the work from discovery and assessment through implementation and adoption.
Sample engagements may include:
- Gift processing redesign. Assess a development team's gift entry and acknowledgment process in Raiser's Edge NXT, clean up the underlying data and configuration, and build automations that cut acknowledgment turnaround time.
- Organizational AI readiness. Assess how teams across an organization use (or avoid) AI, recommend a governance policy, and deliver a prioritized roadmap and staff training.
- Program inquiry automation. Map how a program team handles incoming inquiries, deploy an AI tool to route requests and draft responses, and train staff to manage it.
Client Leadership
- Serve as a day-to-day contact for clients, and as primary contact in the Director's absence, building strong relationships with development teams, operations staff, and technical stakeholders.
- Maintain work plans, timelines, and project dashboards, ensuring deliverables are met within scope, budget, and deadlines.
- Attend client meetings and present deliverables, including assessment findings, process maps, and implementation updates.
- Ensure client-facing materials, including assessment reports, roadmaps, and technical documentation, are client-ready before Director review and approval.
- Stay current on nonprofit technology and AI trends and bring relevant insights to client strategies.
- Support the Director and Impact Officers in identifying opportunities for contract renewals and expanded advisory, implementation, or training services.
- Lead less complex engagements independently, where appropriate.
AI Assessment & Strategy
- Facilitate discovery conversations and stakeholder interviews to assess organizational readiness, workflow pain points, and opportunities for automation.
- Conduct assessments in partnership with the Director, including process mapping, system evaluation, and feasibility analysis.
- Audit and document client workflows, including building documentation from scratch for processes that are currently undocumented.
- Evaluate development operations against fundraising best practices, including gift entry and processing, acknowledgment and stewardship, moves management, prospect research, donor data management, and reporting.
- Assess the health of fundraising CRMs such as Salesforce and Raiser's Edge NXT, identifying configuration, data, and process issues.
- Identify high-impact opportunities for automation and AI integration across development, operations, finance, and program functions.
- Contribute to roadmaps that prioritize solutions by impact, feasibility, cost, and change readiness.
- Support clients in applying responsible AI practices, including governance, policy, and data privacy.
Solution Design & Implementation
- Design, build, and deploy automations and AI-enabled workflows using platforms such as Zapier, Make, or Power Automate.
- Integrate client systems through APIs, webhooks, and data flows, including CRM and fundraising platforms such as Salesforce and Raiser's Edge NXT.
- Configure and deploy AI tools and agents (e.g., Claude, ChatGPT, Microsoft Copilot), including prompt design and custom workflows tailored to client teams.
- Test and validate solutions before rollout, with attention to data quality, security, and privacy, so errors are not automated at scale.
- Collaborate with client technology teams and vendors to ensure secure, responsible, and effective integration of AI solutions.
- Coordinate with other Orr Group team members when a build calls for additional insights or validation.
Adoption & Change Management
- Design and deliver training for client staff on new tools and workflows.
- Identify and build internal champions within client organizations, address resistance, and lead change management to drive adoption.
- Create runbooks, process documentation, and handoff materials so client teams can maintain and support solutions after the engagement ends.
- Track and report on outcomes, including time savings, adoption, and return on investment.
Project Team & Practice Contributions
- Oversee the work of Associates and Associate Directors on client teams, delegating tasks and ensuring work plans and materials are maintained.
- Mentor and coach junior staff, serving as a resource on fundraising operations, systems, and AI tools.
- Contribute to the service line's methodology, including assessment frameworks, tools, templates, and SOPs.
- Support business development by contributing to proposals and scoping, as needed.
- Help build AI and automation fluency across Orr Group by sharing tools, learnings, and training with colleagues.
Qualifications
Required
- Bachelor's degree.
- 6+ years of professional experience, including at least 3 years supporting nonprofit development operations, advancement services, fundraising CRM administration, or nonprofit consulting.
- Hands-on administration experience with at least one fundraising CRM
- Hands-on fluency with automation platforms and working knowledge of APIs, webhooks, and data integration.
- Working knowledge of fundraising best practices across gift processing, acknowledgment, moves management, donor data management, and reporting.
- Proven experience designing, building, and deploying automation or AI solutions from concept through rollout.
- Experience with AI/LLM tools, including prompt design and agentic workflows.
- Strong project management skills, with the ability to manage multiple projects and stakeholders in a deadline-driven environment.
- Ability to move between fundraising and technical conversations, translating in both directions for non-technical leaders and technical staff.
- Strong facilitation, written, and verbal communication skills.
- Sound judgment and discretion around responsible AI and donor data.
- Flexibility to work varying hours as needed to meet client deadlines.
Preferred
- Experience in a client-facing consulting or advisory role.
- Salesforce (Nonprofit Cloud Consultant, Administrator) or Blackbaud certifications.
- Experience applying automation within nonprofits beyond development.
- Experience supporting organizational change initiatives across departments.
Additional Information
Location
Orr Group offices are located in Washington, DC, and New York City, and candidates must be based in either metropolitan area. Our hybrid policy requires staff to spend at least 60% of their working time in an Orr Group office or at client sites.
Salary Range
The salary range for this role is $80,000 - $100,000, with annual bonus potential of up to $10,000.
Benefits
The comprehensive benefits package includes health, dental, and vision plans, a 401(k) retirement plan with employer match, paid holidays, and generous paid time off.
Orr Group Careers
At Orr Group, we recognize that diversity strengthens our impact. We actively seek team members from diverse backgrounds, perspectives, and lived experiences to better serve our clients and the communities they support. We are committed to fostering an inclusive environment where all employees can thrive, contribute, and grow.
Our goal is to attract, develop, and retain exceptional people and create a work environment that is dynamic, rewarding, and enables each of us to realize our potential. We are deeply committed to providing advancement opportunities, mentorship, and the resources you need to explore your talents and aspirations. At Orr Group, we believe in investing in our employees' growth – whether through ongoing professional development, exposure to a wide range of high-impact projects, or the opportunity to collaborate with colleagues across all levels.
Working at Orr Group means being part of a passionate, supportive, and team-oriented environment. You'll work alongside bright, humble, and friendly colleagues who are as dedicated to achieving exceptional results as they are to fostering a positive, collaborative atmosphere. While our work can be challenging and high-pressure, it is also incredibly rewarding. We are driven by a shared mission to solve some of the world's greatest challenges, and you will have the opportunity to make a meaningful impact as part of a diverse and dynamic team.
Orr Group is an Equal Opportunity Employer.
Salary Context
This $80K-$100K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $178K across 2239 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 11,520 AI roles we're tracking, AI/ML Engineer positions make up 76% of the market. At Orr Group, 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 $212,040 based on 13,780 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200. This role's midpoint ($90K) sits 58% below the category median. Disclosed range: $80K to $100K.
Across all AI roles, the market median is $213,480. Top-quartile compensation starts at $264,000. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($266,050) and AI Engineering Manager ($253,461). By seniority level: Entry: $112,320; Mid: $193,200; Senior: $230,000; Director: $272,250; VP: $235,830.
Orr Group AI Hiring
Orr Group has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in New York, NY, US. Compensation range: $100K - $100K.
Location Context
AI roles in New York pay a median of $221,000 across 3,257 tracked positions. That's 4% above the national 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 11,520 open positions tracked in our dataset. By seniority: 140 entry-level, 5,630 mid-level, 4,176 senior, and 1,574 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (708 positions). The remaining 10,737 roles require on-site or hybrid attendance.
The market median for AI roles is $213,480. Top-quartile compensation starts at $264,000. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($266,050 median, 70 roles); AI Engineering Manager ($253,461 median, 58 roles); Research Engineer ($252,000 median, 476 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 11,520 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (8,769), AI Software Engineer (586), AI Product Manager (511). 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 (140) are outnumbered by mid-level (5,630) and senior (4,176) 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 1,574 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (708 positions), with 10,737 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 $213,480. Top-quartile roles start at $264,000, and the 90th percentile reaches $318,400. 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 $266,050 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 (2,267 postings), Aws (1,178 postings), Azure (972 postings), Rag (924 postings), Gcp (715 postings), Pytorch (586 postings), Claude (572 postings), Kubernetes (559 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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