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Job Title: AI Business Manager
PS Job Title: AI Business Manager
Work Place Flexibility: Hybrid
Legal Entity: Entergy Services, LLC
\*\*\*The preferred location for position is New Orleans, other locations will be considered\*\*\*
JOB SUMMARY/PURPOSE
The AI Business Manager is the primary liaison to assigned business functions, responsible for identifying where AI can improve processes and deliver measurable value. The role partners with business leaders as both advisor and implementation lead. As an advisor, the manager helps leaders understand AI capabilities and jointly develop an AI business plan and project pipeline. As an implementation partner, the manager oversees AI project execution with the AI organization to ensure expected business outcomes are achieved. This requires operating as part of the business leadership team, maintaining a deep understanding of business needs, and providing ongoing strategic guidance. Strong, trust\-based relationships with leaders across each business function are essential. The AI Business Manager regularly works with those leaders to identify and prioritize opportunities and maintain an evolving AI Business Integration Roadmap. Success requires close collaboration with peer AI groups in governance, enablement, platform, and delivery to ensure AI products consistently meet customer expectations. As the internal customer advocate, the manager monitors satisfaction and drives improvements in AI products and services. Although not required to be a technical expert, the AI Business Manager must understand the range of AI solutions available—including analytics, automation, and generative AI—so they can advise on which solutions can best address business problems and advance business objectives.
JOB DUTIES/RESPONSIBILITIES
Business Partnership, Engagement \& Value Delivery
· Serve as the primary point of contact between business leaders and the AI organization.
· Conduct discovery sessions to understand business pain points, regulatory constraints, operational priorities, and workflow challenges.
· Translate business needs into AI\-enabled use cases, value cases, and actionable roadmaps.
· Maintain a robust pipeline of AI opportunities aligned with utility operational realities (grid reliability, safety, affordability, and compliance).
· Prepare and contribute to business cases, steering committee materials, project updates, and leadership briefings.
Execution Support \& Governance
· Work closely with Enterprise Data \& AI Delivery teams to ensure projects meet business expectations and regulatory requirements.
· Support change management, user readiness, adoption planning, and post\-launch success monitoring.
· Ensure adherence to responsible AI, governance standards, and compliance frameworks.
Enablement \& AI Adoption
· Champion AI literacy across business units; help leaders and teams understand AI capabilities, limitations, workflows, and value.
· Identify champions, coordinate learning, and drive adoption of enterprise AI tools.
· Contribute to scalable engagement playbooks and repeatable approaches for utility business functions.
Relationship Management
· Build long\-term strategic relationships with leaders across business functions.
· Identify opportunities for enterprise reuse and coordinate cross\-functional collaboration for AI solutions.
· Act as a trusted advisor in navigating operational change in a regulated utility environment.
MINIMUM REQUIREMENTS
Minimum education required of the position
Bachelor’s degree in Business, Engineering, Information Systems, Data Analytics, or related field required OR in lieu of degree minimum 12\+ years of professional experience is required. Master’s degree is preferred.
Minimum experience required of the position
· Minimum 8\+ years of professional experience leading diverse project or product teams to accomplish specific, measurable outcomes. Utility experience preferred.
· Proven experience with AI, automation, analytics, or digital solutions delivery.
· Knowledge and experience with project management and/or process improvement tools and methods is a plus (e.g. Lean, Six\-Sigma, Agile, Process Mapping, Intelligent Automation, Analytics).
· Demonstrated experience consulting with senior \& executive leaders, including identifying needs, developing comprehensive plans, identifying deliverables and presenting results/recommendations to enable outcomes.
Minimum knowledge, skills and abilities required of the position
· Strong ability to translate business needs into AI\-enabled solutions.
· Exceptional communication and relationship building skills with senior stakeholders.
· Solid understanding of AI concepts (machine learning, automation, GenAI, predictive analytics).
· Ability to drive change in environments with evolving technology maturity.
· Comfort navigating ambiguity and shaping structured solutions in dynamic settings.
· Experience with governance processes, risk management, and cross\-functional coordination.
Any certificates, licenses, etc. required for the position
Program Management Professional (PMP) certification preferred.
OTHER ATTRIBUTES
Functional Knowledge
In depth understanding of project management methodology, from initial scoping to final delivery and user adoption.
Business Expertise
Strong knowledge of business requirements for aligned business unit and how business needs are will shift over time.
Leadership
Proven leadership skills in building, leading, and motivating high\-performing teams.
Problem Solving
Able to resolve complex problems, especially with translating business requirement to functional and operational capability and to keep projects on track.
Impact
Deliver new projects and programs to business units and ensure that the final outcome meets their needs.
Interpersonal Skills
Able to coordinate to multiple stakeholders, cross\-functional team members, while building consensus on desired outcomes. Effectively resolves conflicts and disagreements within the team.
WORKING CONDITIONS/ESSENTIAL FUNCTIONS/PHYSICAL REQUIREMENTS
Office environment with minimal physical requirements. As a provider of essential services, Entergy expects its employees to be available to work additional hours, to work in alternate locations, and/or to perform additional duties in connection with storms, outages, emergencies, or other situations as deemed necessary by the company. Exempt employees may not be paid overtime associated with such duties.
OTHER
- Not all aspects of the job are covered by the description – may require “other duties as assigned”
- Job may change over time in accordance with business needs
- Job description does not guarantee employment
\#LI\-DG1 \#LI\-HYBRID
Primary Location: Louisiana\-New Orleans Louisiana : New Orleans \|\| Texas : Woodlands
Job Function: Corporate
FLSA Status: Professional
Relocation Option:
Union description/code: NON BARGAINING UNIT
Number of Openings: 1
Req ID: 124015
PS Job Title: AI Business Manager
Travel Percentage:25% to 50%
An Equal Opportunity Employer, Minority/Female/Disability/Vets.
EEO Statement: The Entergy System of Companies provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, gender, sexual orientation, gender identity or expression, national origin, age, disability, genetic information, marital status, amnesty, or status as a protected veteran in accordance with applicable federal, state and local laws. The Entergy System of Companies complies with applicable state and local laws governing non\-discrimination in employment in every location in which the company has facilities. This policy applies to all terms and conditions of employment including, but not limited to, recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.
The Entergy System of Companies expressly prohibits any form of unlawful employee harassment based on race, color, religion, sex, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. Improper interference with the ability of the Entergy System of Company employees to perform their expected job duties is absolutely not tolerated.
Accessibility: Entergy provides reasonable accommodations for online applicants. Requests for a reasonable accommodation may be made orally or in writing by an applicant, employee, or third party on his or her behalf. If you are an individual with a disability and you are in need of an accommodation for the recruiting process please provide your name, contact number, the accommodation requested and the requisition number that you are requesting the accommodation for. Employee Services will contact you regarding your request.
Additional Responsibilities: As a provider of essential services, Entergy expects its employees to be available to work additional hours, to work in alternate locations, and/or to perform additional duties in connection with storms, outages, emergencies, or other situations as deemed necessary by the company. Exempt employees may not be paid overtime associated with such duties.
Know Your Rights: Workplace Discrimination is Illegal
The non\-confidential portions of the affirmative action program for individuals with disabilities and protected veterans shall be available for inspection upon request by any employee or applicant for employment. Please contact [email protected] to schedule a time to review the affirmative action plan during regular office hours.
WORKING CONDITIONS:
As a provider of essential services, Entergy expects its employees to be available to work additional hours, to work in alternate locations, and/or to perform additional duties in connection with storms, outages, emergencies, or other situations as deemed necessary by the company. Exempt employees may not be paid overtime associated with such duties.
Please note: Authorization to work in the United States is a precondition to employment in this position. Entergy will not sponsor candidates for work visas for this position.
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 Entergy, 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 in Demand for This Role
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. Mid-level AI roles across all categories have a median of $200,000.
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.
Entergy AI Hiring
Entergy has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in New Orleans, LA, US.
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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