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Responsible AI Team Lead/Consultant \| Mid\-Level \| Full time
Job No. R00335827 \| Multiple Locations
We Are:
Accenture’s Global Responsible AI team within the Global Data \& AI Practice. AI is becoming more pervasive, more powerful, and more accessible. With these new opportunities come increased risks. We work with leading organizations to ensure AI is designed, built, and deployed in a manner that engenders trust and adheres to laws, regulations and ethical norms. Our Responsible AI strategy will enable us to embed responsibility into all of Accenture’s data and AI activities. We’re developing and deploying differentiated IP and Responsible AI solutions with our ecosystem partners. We’ll be engaging regulators to help shape the policy agenda, conducting pioneering research with academia and offer training and resources to our clients through the Responsible AI Academy. The risks of AI are real and well\- known. Let’s help our clients turn those risks into opportunities.
You are:
We are seeking experts who have a deep understanding of policy, standards, and regulation of AI, and who can translate this into helping our clients establish their principles, policies, operating model, governance structures and controls for Responsible AI. The ideal candidate will enjoy the breadth and pace of working with clients from different sectors and will also have the capability to step back and help Accenture shape and influence the development of AI standards and policies. You'll learn, grow and advance in an innovative culture that thrives on shared success, diverse ways of thinking and enables boundaryless opportunities that can drive your career in new and exciting ways.
The work:
- Engaging with prospective clients to help sell Responsible AI projects.
- Shaping and leading client projects for Responsible / Ethical AI with a focus on policy, standards and regulatory advisory, operating model, governance structures and controls
- Act as subject matter expert for Responsible AI within a data science / data transformation team.
- Supporting client sales conversations and proposals
- Delivering client projects and managing projects related to Responsible AI
- Communicating and providing guidance to senior Accenture leadership and client teams
- Assessing the latest developments in data and AI policy and standards
- Creating and maintaining an overview of the key developments in AI regulation
- Engaging with key stakeholders within the policy and regulatory space
- Presenting and positioning Accenture’s point of view amongst clients and other key stakeholders
Travel may be required for this role. The amount of travel will vary from 0 to 100% depending on business need and client requirements.
Here’s what you need:
Minimum of 5 years’ experience in management consulting. Consulting experience should include at least one of the following:
- Experience in government/legislative development bodies, regulators, standards bodies, in designing and implementing operating models, risk management controls, governance structures and controls in any of these areas, or multilateral collaborative groups
- As a member of a corporate team focused on Responsible AI
- As an academic focused not just on the theory but also on the practical application of Responsible AI
- Exposure to data science strategy, machine learning, and business analytics to solve business problems
Minimum of 2\-3 years’ experience with Data and AI Regulation should include, but not limited to:
- Experience in government/legislative development bodies, regulators, standards bodies, or multilateral collaborative groups
Bachelor's degree or equivalent (minimum 12 years) work experience. (If Associate’s Degree, must have minimum 6 years work experience)
Priority skills/knowledge:
- Data \& AI regulations, compliance, and standards knowledge
- Responsible AI
- Generative AI risk, controls, and mitigations
- Stakeholder Management
- Risk assessment
- Project management (if manager or above)
- Consulting skills designing and implementing operating models, governance structures and controls
Bonus points if you have:
- Published academic papers, white papers, or some form of thought leadership in the field of Responsible / Ethical AI, or closely related areas (advantageous)
- Legal experience (if the Req POC is needing an RAI Legal/Compliance SME)
- Ability to lead project workstreams to completion
- Ability to manage resources in a matrix organization
Compensation at Accenture varies depending on a wide array of factors, which may include but are not limited to the specific office location, role, skill set, and level of experience. As required by local law, Accenture provides a reasonable range of compensation for roles that may be hired as set forth below. We anticipate this job posting will be posted until 07/26/2026\. Accenture offers a market competitive suite of benefits including medical, dental, vision, life, and long\-term disability coverage, a 401(k) plan, bonus opportunities, paid holidays, and paid time off. See more information on our benefits here:
U.S. Employee Benefits \| Accenture
Role Location Annual Salary Range California $70,350 to $205,800 Cleveland $59,100 to $164,600 Colorado $63,800 to $177,800 District of Columbia $68,000 to $189,300 Illinois $59,100 to $177,800 Maine $54,400 to $151,400 Maryland $63,800 to $177,800 Massachusetts $63,800 to $189,300 Minnesota $63,800 to $177,800 New York $66,300 to $205,800 New Jersey $68,000 to $205,800 Virginia $59,100 to $189,300 Washington $80,200 to $189,300
New York City, NY
Boston, MA
Chicago, IL
San Francisco, CA
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Salary Context
This $59K-$205K range is in the lower quartile for AI Safety roles in our dataset (median: $254K across 6 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 1,809 AI roles we're tracking, AI Safety positions make up 0% of the market. At Logic, Inc., 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 in Demand for This Role
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 Safety roles pay a median of $274,200 based on 57 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $165,778. This role's midpoint ($132K) sits 52% below the category median. Disclosed range: $59K to $205K.
Across all AI roles, the market median is $200,700. Top-quartile compensation starts at $254,000. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($268,700) and Research Engineer ($260,000). By seniority level: Entry: $97,760; Mid: $165,778; Senior: $227,400; Director: $250,000; VP: $250,000.
Logic, Inc. AI Hiring
Logic, Inc. has 6 open AI roles right now. They're hiring across AI Safety, AI/ML Engineer. Positions span New York, NY, US, Irving, TX, US, Columbus, OH, US. Compensation range: $168K - $338K.
Location Context
AI roles in New York pay a median of $211,000 across 2,760 tracked positions. That's 5% above the national median.
Career Path
Common paths into AI Safety 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 1,809 open positions tracked in our dataset. By seniority: 34 entry-level, 797 mid-level, 728 senior, and 250 leadership roles (Director, VP, C-Level). Remote roles make up 16% of the market (294 positions). The remaining 1,505 roles require on-site or hybrid attendance.
The market median for AI roles is $200,700. Top-quartile compensation starts at $254,000. The 90th percentile reaches $307,500. Highest-paying categories: AI Safety ($274,200 median, 57 roles); AI Engineering Manager ($268,700 median, 42 roles); Research Engineer ($260,000 median, 442 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 1,809 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (1,274), Data Scientist (145), AI Software Engineer (132). 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 (34) are outnumbered by mid-level (797) and senior (728) 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 250 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 16% of all AI roles (294 positions), with 1,505 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 $200,700. Top-quartile roles start at $254,000, and the 90th percentile reaches $307,500. 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 $274,200 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 (877 postings), Aws (592 postings), Azure (458 postings), Rag (380 postings), Gcp (364 postings), Pytorch (277 postings), Prompt Engineering (266 postings), Claude (250 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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