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About This Role
Description/Job Summary
Be part of a team focused on enabling the success of Farm Credit East’s staff through world class technology support. Farm Credit East’s success is built on its ability to leverage technology and staff to provide a high-class customer and employee experience. This position provides staff the support and resources they need to provide the level of service Farm Credit East is known for. We are One Team Working Together with a focus on our five pillars: Outstanding Customer and Employee Experience, Quality Growth, Operational Excellence, Commitment to our Communities, and Protecting Customer Information.
The Enterprise AI & Platform Administrator plays a critical role in enabling the organization’s adoption and governance of Microsoft 365, Copilot Studio, and enterprise AI technologies. This position is responsible for ensuring secure, efficient, and compliant management of AI platforms, while supporting innovation and operational excellence across the organization.
The value drivers for this role are as follows:
- Enable secure and scalable adoption of enterprise AI and Microsoft 365 platforms
- Strengthen governance, compliance, and operational insights through reporting and collaboration
Duties and Responsibilities:
Permissions & Access Management
- Work collaboratively with internal and external stakeholders to review roles across Microsoft 365, Power Platform, SharePoint, and Active Directory.
- Ensure security controls are least‑privilege access, conduct periodic access reviews, and ensure secure delegation.
- Understand and collaborate on Entra ID agent identity settings and group‑based access for AI agents.
Environment & Capacity Administration
- Understand develop and maintain Copilot Studio environments, including policies, capacity planning, and compliance settings.
- Oversee environment lifecycle management (ALM) and ensure readiness for agent deployment..
- Work collaboratively to deploy new Microsoft AI capabilities(Anthropic, CoWork, etc…) and models to the Enterprise in a secure and effective manner.
AI Agent Lifecycle & Availability
- Develop, approve, publish, and manage availability of AI agents for organization‑wide or targeted audiences.
- Partner with makers, environment admins, and site owners to ensure agents meet organizational standards and are properly surfaced across Microsoft 365, Teams, and SharePoint.
SharePoint & Active Directory Administration
- Work collaboratively with stakeholders of SharePoint sites to ensure controls used for agent deployment and governance.
- Understand Active Directory security groups, user roles, and agent discoverability and assist in improvements to security governance.
Reporting & Metrics
- Produce reports and dashboards on agent deployment, usage, compliance, and performance.
- Provide KPIs and insights to support leadership, governance, and continuous improvement.
Governance, Security & Compliance
- Ensure best practices for access control, centralized group management, and quarterly audits.
- Maintain documentation, change logs, and governance artifacts to ensure transparency and accountability.
- Support responsible AI practices and adherence to regulatory expectations.
Job Qualifications and Requirements:
- This position requires a Bachelor's degree in Computer Science, Business, or a related field with solid understanding of computer and business process skills specific to a financial institution.
- Knowledge of Microsoft 365, Power Platform, SharePoint, Active Directory
- We offer hybrid work options after two weeks of employment with Farm Credit East. Hybrid work options are determined based on job role and balancing the needs of the customers, the team, and individual work performance. This will be reviewed based on manager discretion.
Compensation and Benefits:
- Salary range: $95,000 - $115,000 commensurate with experience.
- Short Term Incentive to reward business results
- Retirement Contributions: + 401(k) match up to 6% of salary; or for those unable to take full advantage of the 401(k) match, verified student loan payments may qualify for an employer match in your 401(k) up to 6% of salary + Defined Contribution retirement plan funded at 2-9% of salary depending on years of service
- Time Off: + 15-25 days of vacation leave per year, depending on years of service + 12 days of holiday leave per year + 7.5 days of sick leave in your first year, followed by 12 days of sick leave per year thereafter; unlimited rollover of unused sick leave year to year + Paid Parental Leave: Up to 80 hours of paid leave for birthing, non-birthing, and adoptive parents + Family Care Leave: Additional leave options available under FMLA and company policy
- Health and Insurance: + Comprehensive medical, dental, and vision plans, including preventive care and wellness programs to support your overall health and well-being + Health Savings Account + Life insurance at 2x base pay + Accidental Death and Dismemberment insurance at 2x base pay + Long-term disability insurance at 2/3 base pay
- Additional Benefits: + Tuition reimbursement + Continuing education and training + Employee Assistance Program offering a wide variety of tools and resources
- Benefits Eligibility: + Eligibility Begins: First of the month following your hire date + Eligible Employees: Full-time employees working 30+ hours per week; Part-Time employees working 20+ hours per week.
Farm Credit East is an Equal Opportunity Employer. As an Equal Opportunity Employer, we do not discriminate on the basis of race, color, religion, national origin, sex, sexual orientation, gender identity, age, marital status, disability status, protected veteran status, genetic information or any other status protected by federal, state or local law. It is our goal to make employment decisions that further the principle of equal employment opportunity by utilizing objective standards based upon an individual's qualifications for a specific job opening. In compliance with the Americans with Disabilities Act (“ADA”), if you have a disability and would like a reasonable accommodation in order to apply for a position with Farm Credit East, please call 1-800-562-2235 or e-mail [email protected].
Salary Context
This $95K-$115K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $178K across 1623 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 9,079 AI roles we're tracking, AI/ML Engineer positions make up 76% of the market. At Farm Credit East, 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 $211,950 based on 13,048 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200. This role's midpoint ($105K) sits 50% below the category median. Disclosed range: $95K to $115K.
Across all AI roles, the market median is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($256,000) and Research Engineer ($252,000). By seniority level: Entry: $111,000; Mid: $193,200; Senior: $229,300; Director: $272,300; VP: $235,830.
Farm Credit East AI Hiring
Farm Credit East has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Lebanon, NJ, US. Compensation range: $115K - $115K.
Location Context
Across all AI roles, 6% (531 positions) offer remote work, while 8,478 require on-site attendance. Top AI hiring metros: New York (3,078 roles, $221,000 median); San Francisco (2,646 roles, $261,000 median); Los Angeles (1,486 roles, $210,000 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 9,079 open positions tracked in our dataset. By seniority: 106 entry-level, 4,384 mid-level, 3,343 senior, and 1,246 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (531 positions). The remaining 8,478 roles require on-site or hybrid attendance.
The market median for AI roles is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($256,000 median, 66 roles); Research Engineer ($252,000 median, 457 roles); AI Engineering Manager ($251,622 median, 55 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 9,079 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,862), AI Product Manager (453), AI Software Engineer (451). 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 (106) are outnumbered by mid-level (4,384) and senior (3,343) 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 1,246 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (531 positions), with 8,478 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 $213,000. Top-quartile roles start at $263,911, 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 $256,000 median, while Prompt Engineer roles sit at $141,440. 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 (1,649 postings), Aws (898 postings), Azure (723 postings), Rag (671 postings), Gcp (536 postings), Pytorch (434 postings), Claude (410 postings), Kubernetes (406 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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