Interested in this AI Consultant role at NTT DATA?
Apply Now →Skills & Technologies
About This Role
Req ID: 381440
NTT DATA strives to hire exceptional, innovative and passionate individuals who want to grow with us. If you want to be part of an inclusive, adaptable, and forward\-thinking organization, apply now.
We are currently seeking a AI Consultant \- Banking to join our team in Plano, Texas (US\-TX), United States (US).
AI Consultant NTT DATA is a trusted global innovator of business and technology services, helping clients innovate, optimize, and transform for success. We strive to hire exceptional, innovative, and passionate individuals who want to grow with us. If you want to be part of an inclusive, adaptable, and forward\-thinking organization, apply now.
Overview:
The AI Consultant is a client\-facing advisor within the AI Go\-to\-Market organization responsible for identifying, shaping, and mobilizing AI transformation opportunities. This role combines strategy acumen, AI fluency, structured consulting methods, and commercial orientation to help clients define AI value cases, operating models, roadmaps, and adoption approaches. The AI Consultant partners with AI Architects, Forward\-Deployed Engineering, Delivery, Sellers, ecosystem partners, and Geo and Industry leaders to convert client priorities into qualified opportunities and successful engagements.
Key Responsibilities:
- Act as a trusted client advisor to identify AI transformation opportunities, business pain points, and value cases.
- Shape AI strategy, target operating model, governance, adoption, responsible AI, and transformation roadmaps for clients.
- Translate client needs into practical AI solutions in partnership with architects, FDE, delivery, and partner teams.
- Develop proposals, business cases, ROI models, proof\-of\-concept plans, and executive\-ready client materials.
- Support opportunity qualification, deal shaping, solutioning, mobilization, and transition into delivery.
- Lead and support structured consulting activities, including workshops, stakeholder interviews, assessments, prioritization exercises, and roadmap development.
- Bring a strategic lens to client conversations, connecting AI use cases to operating model change, business outcomes, adoption, and measurable enterprise value.
- Reuse and improve global GTM assets, offering content, credentials, delivery patterns, and client\-facing narratives.
- Stay current on AI, agentic AI, enterprise adoption trends, responsible AI, and partner capabilities to strengthen client advisory quality.
Success Measures:
- Personal sales contribution or qualified pipeline contribution, as applicable by career level.
- Utilization or billability against target.
- Quality of client deliverables, proposal contribution, stakeholder feedback, and reuse of global GTM assets.
- Contribution to downstream implementation opportunities and successful client mobilization.
Basic Qualifications:
- 5\+ years of professional experience in consulting, professional services, strategy, transformation, AI, data, analytics, or related client\-facing roles.
- 3\+ years of experience shaping or delivering AI, data science, machine learning, GenAI, agentic AI, analytics, or digital transformation initiatives. Experience may be demonstrated through client delivery, on\-the\-job AI work, a data science background, or an advanced degree.
- Demonstrated strategy acumen, including business model analysis, operating model design, value case development, transformation planning, and executive narrative development.
- Experience supporting presales activities such as opportunity identification, solution shaping, proposal development, business case creation, or executive\-level deal reviews.
- Working knowledge of enterprise AI concepts, including LLMs, AI agents, RAG, ML lifecycle, data readiness, responsible AI, governance, and adoption considerations.
- Bachelor's degree or equivalent work experience.
Preferred Skills:
- Master's degree, MBA, data science degree, AI/ML certification, or equivalent practical AI experience.
- Experience in one or more industries such as financial services, insurance, manufacturing, healthcare and life sciences, public sector, automotive, or commercial sectors.
- Familiarity with cloud and AI platforms such as Azure, AWS, GCP, OpenAI, Anthropic, Mistral, Google/Gemini, Databricks, or Snowflake.
- Strong executive communication
NTT DATA provides a reasonable range of compensation for U.S.\-based positions. The starting pay range for this remote role is $104,240\.00\-$156,360\.00\. This range reflects the minimum and maximum target compensation for the position across all US locations. Actual compensation will depend on a number of factors, including the candidate’s actual work location, relevant experience, technical skills, and other qualifications.
This position may also be eligible for incentive compensation based on individual and/or company performance.
This position is eligible for company benefits including medical, dental, and vision insurance with an employer contribution, flexible spending or health savings account, life and ADD insurance, short and long term disability coverage, paid time off, employee assistance, participation in a 401k program with company match, and additional voluntary or legally\-required benefits.
About NTT DATA
NTT DATA is a $30 billion business and technology services leader, serving 75% of the Fortune Global 100\. We are committed to accelerating client success and positively impacting society through responsible innovation. We are one of the world's leading AI and digital infrastructure providers, with unmatched capabilities in enterprise\-scale AI, cloud, security, connectivity, data centers and application services. our consulting and Industry solutions help organizations and society move confidently and sustainably into the digital future. As a Global Top Employer, we have experts in more than 50 countries. We also offer clients access to a robust ecosystem of innovation centers as well as established and start\-up partners. NTT DATA is a part of NTT Group, which invests over $3 billion each year in RD.
Whenever possible, we hire locally to NTT DATA offices or client sites. This ensures we can provide timely and effective support tailored to each client’s needs. While many positions offer remote or hybrid work options, these arrangements are subject to change based on client requirements. For employees near an NTT DATA office or client site, in\-office attendance may be required for meetings or events, depending on business needs. At NTT DATA, we are committed to staying flexible and meeting the evolving needs of both our clients and employees. NTT DATA recruiters will never ask for payment or banking information and will only use @nttdata.com, @nttdatafed.com and @talent.nttdataservices.com email addresses. If you are requested to provide payment or disclose banking information, please submit a contact us form, https://us.nttdata.com/en/contact\-us.
NTT DATA endeavors to make https://us.nttdata.com accessible to any and all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process, please contact us at https://us.nttdata.com/en/contact\-us. This contact information is for accommodation requests only and cannot be used to inquire about the status of applications. NTT DATA is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status. For our EEO Policy Statement, please click here. If you'd like more information on your EEO rights under the law, please click here. For Pay Transparency information, please click here.
Salary Context
This $104K-$156K range is above the median for AI Consultant roles in our dataset (median: $130K across 5 roles with salary data).
Role Details
About This Role
This role sits at the intersection of AI and engineering, building systems that bring machine learning capabilities into production environments. The scope varies by company, but the common thread is applying AI technology to solve real business problems at scale. Most AI roles today require a combination of software engineering fundamentals and domain-specific ML knowledge, with the exact mix depending on the team's maturity and the product they're building.
The AI job market is evolving fast. New role categories emerge as companies figure out what they need to ship AI-powered products. What matters most is the ability to learn quickly, build working systems, and iterate based on real-world performance data. The specific title matters less than the skills you bring and the problems you can solve. Companies are past the experimentation phase and want engineers who can deliver production-quality systems that work reliably at scale.
Across the 3,708 AI roles we're tracking, AI Consultant positions make up 0% of the market. At NTT DATA, this role fits into their broader AI and engineering organization.
AI hiring keeps growing across industries. Companies in tech, finance, healthcare, and retail are all building AI teams. The strongest demand is for people who can bridge the gap between AI research and production engineering. The shift toward generative AI has created new role types (LLM Engineer, Prompt Engineer, AI Agent Developer) that didn't exist three years ago, while traditional roles (Data Scientist, ML Engineer) have evolved to incorporate LLM capabilities.
What the Work Looks Like
Day-to-day work involves a mix of building, debugging, and collaborating. You'll write code, review pull requests, participate in design discussions, and work with cross-functional teams (product, design, data) to define what AI features should do and how they should behave. Expect to spend time on both technical implementation and communication. Most AI teams operate in two-week sprint cycles, with regular demos and retrospectives. The ratio of heads-down coding to meetings and reviews varies by seniority, with senior roles spending more time on architecture decisions and mentorship.
AI hiring keeps growing across industries. Companies in tech, finance, healthcare, and retail are all building AI teams. The strongest demand is for people who can bridge the gap between AI research and production engineering. The shift toward generative AI has created new role types (LLM Engineer, Prompt Engineer, AI Agent Developer) that didn't exist three years ago, while traditional roles (Data Scientist, ML Engineer) have evolved to incorporate LLM capabilities.
Skills Required
Python and cloud platform experience are common requirements. Specific skill needs vary by company and focus area, but familiarity with ML frameworks, data pipelines, and API design covers the basics for most roles. RAG (Retrieval-Augmented Generation), vector databases, and LLM API integration are increasingly standard requirements across role types.
Beyond the core stack, communication skills matter more than many technical candidates realize. The ability to explain AI capabilities and limitations to non-technical stakeholders is a differentiator at every level. Technical writing, documentation, and clear thinking about tradeoffs are underrated skills in AI roles. Experience with evaluation methodology (how to measure whether an AI system is working well) is becoming a core requirement, especially for roles that involve LLM integration.
Look for job postings that specify the problems you'll work on, the tech stack, and the team structure. Vague postings that list every AI buzzword are often a sign the company hasn't figured out what they need. Strong postings describe the product context, the team you'd join, and the specific challenges you'd tackle.
Compensation Benchmarks
AI Consultant roles pay a median of $152,604 based on 12 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $200,000. This role's midpoint ($130K) sits 15% below the category median. Disclosed range: $104K to $156K.
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.
NTT DATA AI Hiring
NTT DATA has 14 open AI roles right now. They're hiring across AI Consultant, AI/ML Engineer, AI Architect, Prompt Engineer. Positions span Plano, TX, US, Atlanta, GA, US, Irving, TX, US. Compensation range: $114K - $426K.
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 Consultant roles include Software Engineer, Data Scientist, Data Analyst.
From here, career progression typically leads toward Senior Engineer, AI Architect, Engineering Manager, Principal Engineer.
Focus on building things that work. A deployed project that solves a real problem is worth more than any certification. Contribute to open-source, build portfolio projects, and invest in fundamentals (software engineering, statistics, systems design) rather than chasing the latest framework. The AI field moves fast, but the engineers who succeed long-term are the ones with strong fundamentals who can adapt to new tools and paradigms as they emerge.
What to Expect in Interviews
AI interviews typically combine coding challenges (Python-focused), system design questions tailored to the role, and discussions about your experience with relevant tools and frameworks. Strong candidates demonstrate both technical depth and the ability to make pragmatic engineering tradeoffs. Prepare portfolio projects that demonstrate end-to-end capability rather than isolated skills.
When evaluating opportunities: Look for job postings that specify the problems you'll work on, the tech stack, and the team structure. Vague postings that list every AI buzzword are often a sign the company hasn't figured out what they need. Strong postings describe the product context, the team you'd join, and the specific challenges you'd tackle.
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).
AI hiring keeps growing across industries. Companies in tech, finance, healthcare, and retail are all building AI teams. The strongest demand is for people who can bridge the gap between AI research and production engineering. The shift toward generative AI has created new role types (LLM Engineer, Prompt Engineer, AI Agent Developer) that didn't exist three years ago, while traditional roles (Data Scientist, ML Engineer) have evolved to incorporate LLM capabilities.
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
Get Weekly AI Career Intelligence
Salary data, skills demand, and market signals from 16,000+ AI job postings. Every Monday.