AI Engineering Consultant
for section headings: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule.
We must not repeat job title as heading. No Job ID. Remove boilerplate, navigation, legal, EEO, etc. Keep substantive info.
We need sections only if posting has real specific content.
Let's extract content:
- Intro about Accenture: "We Are Accenture is a leading global professional services company..." This is about company, could be "About the role"? Actually "About the role" maybe includes description of team and mission. Could use "About the role" for the introductory paragraphs describing the practice and what they do.
- Responsibilities: The "The Work" bullet list: Build AI applications, implement LLM patterns, Deploy AI workloads, Engineer with modern tooling, Apply DevOps practices, Travel may be required.
- Requirements/Qualifications: "Here’s What You Need" list: Minimum of 3 years experience in software or AI/ML/LLMs engineering, Minimum of 2 years hands-on experience building AI applications with providers..., Minimum of 2 years experience with Python and API integration, Minimum of 2 years experience with RAG, vector databases, and orchestration frameworks, Minimum of 1 year experience with containerization (Docker/Kubernetes), CI/CD, and cloud security, Bachelor's degree in Computer Science/related field or equivalent (minimum 12 years' work experience). If Associate’s Degree, must have equivalent minimum 6-year work experience.
- Bonus Points: "Bonus Points If You" list: experience serving utilities clients, Master’s degree, Cloud or AI engineering certifications, experience with agentic AI patterns and multi-agent orchestration.
- Compensation: "Compensation at Accenture varies depending on a wide array of factors..." plus salary ranges per location. This is Pay section.
- Benefits: "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." plus link.
- Schedule: Travel may be required for this role, varying from 0 to 80% depending on business need and client requirements. That's schedule? Could be under Schedule section.
We should not include boilerplate like EEO, accommodation request, etc.
We need to output only HTML fragment, no /, no markdown fences.
We'll create sections:
About the role
with paragraphs describing Accenture and AI and Data practice.
Responsibilities
with - items.
Requirements
with - items (the mandatory requirements).
Qualifications
maybe could be same as Requirements? But we have both Requirements and Qualifications sections allowed. Could separate: Requirements = mandatory experience; Qualifications = education? But we already have education in requirements. Could treat Requirements as experience, Qualifications as education + bonus? However instructions: Use headings only when posting has real specific content. We have content for Requirements (experience) and Qualifications (education). Bonus points could be Skills? Actually Skills heading could be for technical skills like Python, API integration, etc. But we already have those in requirements. Could treat Skills as bonus points? Or we could have Skills section for technical skills (Python, API integration, RAG, vector databases, orchestration frameworks, containerization, CI/CD, cloud security). But that overlaps.
Better to follow typical structure: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule.
We have content for:
- About the role: company description and practice.
- Responsibilities: The Work bullet list.
- Requirements: mandatory experience list.
- Qualifications: education requirement (Bachelor's degree etc.) Could also include Associate's degree condition.
- Skills: maybe list of technical skills: Python, API integration, RAG, vector databases, orchestration frameworks (LangChain, LlamaIndex), containerization (Docker/Kubernetes), CI/CD, cloud security, experience with model providers (OpenAI, Anthropic, AWS Bedrock, Azure OpenAI, Google Vertex AI), DevOps practices.
But we already have many of those in requirements. However we can still list them under Skills as a summary.
- Benefits: benefits description.
- Pay: compensation and salary ranges.
- Schedule: travel requirement.
We must not include filler like "commensurate with experience". We have specific salary ranges.
We must not include boilerplate like EEO, accommodation request, etc.
We need to preserve all substantive information; do not invent or summarize away detail.
Thus we need to include the salary ranges per location as listed.
We need to include the link for benefits? The instruction: remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. The benefits link is not boilerplate; it's part of benefits. Should we keep the link? It's a link to benefits page. It's substantive. We can keep it as inside the .
Similarly, we might keep the link for benefits.
We must not include the "See more information on our benefits here: " but we can keep the link.
We must not include the "Requesting an Accommodation" etc.
We must not include the "Equal Employment Opportunity Statement" etc.
We must not include the "Other Employment Statements" etc.
We must not include the "Job candidates will not be obligated to disclose sealed or expunged records" etc.
We must not include the "We work with one shared purpose: to deliver on the promise of technology and human ingenuity." That's at end but maybe part of boilerplate? It's a generic statement; could be considered boilerplate. Safer to remove.
Now craft HTML.
We'll need to escape any special characters inside HTML? Not needed.
We'll produce:
About the role
We Are Accenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services—creating tangible value at speed and scale. We are a talent- and innovation-led company with approximately 790,000 people serving clients in more than 120 countries. Technology is at the core of change today, and we are one of the world’s leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability. Our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song, together with our culture of shared success and commitment to creating 360° value, enable us to help our clients reinvent and build trusted, lasting relationships. We measure our success by the 360° value we create for our clients, each other, our shareholders, partners and communities. Visit us at accenture.com. Our AI and Data practice sits at the intersection of deep industry knowledge and applied AI and data engineering. We help the world’s leading Resources and Utilities organizations reinvent how they run — designing the data foundations, AI platforms, and governance models that turn data into trusted, production-grade intelligence. We are not looking for generalists who advise on AI in the abstract. We need practitioners who understand how enterprises actually operate, where the friction lives, and how to engineer smarter solutions using AI and data to fundamentally transform business processes and outcomes.
Responsibilities
- Build AI applications — develop and integrate AI applications using leading model providers (OpenAI, Anthropic) and cloud platforms (AWS Bedrock, Azure OpenAI, Google Vertex AI).
- Implement LLM patterns — implement RAG, prompt orchestration, evaluation, and guardrails in LLM-powered applications, APIs, and pipelines.
- Deploy AI workloads — deploy and operationalize AI workloads on cloud infrastructure with scalability, security, cost efficiency, and reliability in mind.
- Engineer with modern tooling — use Python, API integration, vector databases, and orchestration frameworks (e.g., LangChain, LlamaIndex) to build production-ready solutions.
- Apply DevOps practices — apply containerization (Docker/Kubernetes), CI/CD, and cloud security best practices across the AI delivery lifecycle.
- Travel may be required for this role, varying from 0 to 80% depending on business need and client requirements.
Requirements
- Minimum of 3 years of experience in software or AI/ML/LLMs engineering.
- Minimum of 2 years of hands-on experience building AI applications with providers such as OpenAI, Anthropic, AWS Bedrock, Azure OpenAI, or Google Vertex AI.
- Minimum of 2 years of experience with Python and API integration.
- Minimum of 2 years of experience with RAG, vector databases, and orchestration frameworks (e.g., LangChain, LlamaIndex).
- Minimum of 1 year of experience with containerization (Docker/Kubernetes), CI/CD, and cloud security.
Qualifications
- Bachelor's degree in Computer Science/related field or equivalent (minimum 12 years' work experience). If Associate’s Degree, must have equivalent minimum 6-year work experience.
Skills
- Experience with leading model providers: OpenAI, Anthropic, AWS Bedrock, Azure OpenAI, Google Vertex AI.
- Proficiency in Python and API integration.
- Experience with RAG, vector databases, and orchestration frameworks (LangChain, LlamaIndex).
- Containerization and orchestration: Docker, Kubernetes.
- CI/CD pipelines and cloud security best practices.
- DevOps practices applied to AI delivery lifecycle.
- Experience with agentic AI patterns and multi-agent orchestration (bonus).
Benefits
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.
Pay
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 08/25/2026.
- 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: $63,80
Requirements
with- items (the mandatory requirements).
Qualifications
maybe could be same as Requirements? But we have both Requirements and Qualifications sections allowed. Could separate: Requirements = mandatory experience; Qualifications = education? But we already have education in requirements. Could treat Requirements as experience, Qualifications as education + bonus? However instructions: Use headings only when posting has real specific content. We have content for Requirements (experience) and Qualifications (education). Bonus points could be Skills? Actually Skills heading could be for technical skills like Python, API integration, etc. But we already have those in requirements. Could treat Skills as bonus points? Or we could have Skills section for technical skills (Python, API integration, RAG, vector databases, orchestration frameworks, containerization, CI/CD, cloud security). But that overlaps. Better to follow typical structure: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We have content for: - About the role: company description and practice. - Responsibilities: The Work bullet list. - Requirements: mandatory experience list. - Qualifications: education requirement (Bachelor's degree etc.) Could also include Associate's degree condition. - Skills: maybe list of technical skills: Python, API integration, RAG, vector databases, orchestration frameworks (LangChain, LlamaIndex), containerization (Docker/Kubernetes), CI/CD, cloud security, experience with model providers (OpenAI, Anthropic, AWS Bedrock, Azure OpenAI, Google Vertex AI), DevOps practices. But we already have many of those in requirements. However we can still list them under Skills as a summary. - Benefits: benefits description. - Pay: compensation and salary ranges. - Schedule: travel requirement. We must not include filler like "commensurate with experience". We have specific salary ranges. We must not include boilerplate like EEO, accommodation request, etc. We need to preserve all substantive information; do not invent or summarize away detail. Thus we need to include the salary ranges per location as listed. We need to include the link for benefits? The instruction: remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. The benefits link is not boilerplate; it's part of benefits. Should we keep the link? It's a link to benefits page. It's substantive. We can keep it as inside the. Similarly, we might keep the link for benefits. We must not include the "See more information on our benefits here: " but we can keep the link. We must not include the "Requesting an Accommodation" etc. We must not include the "Equal Employment Opportunity Statement" etc. We must not include the "Other Employment Statements" etc. We must not include the "Job candidates will not be obligated to disclose sealed or expunged records" etc. We must not include the "We work with one shared purpose: to deliver on the promise of technology and human ingenuity." That's at end but maybe part of boilerplate? It's a generic statement; could be considered boilerplate. Safer to remove. Now craft HTML. We'll need to escape any special characters inside HTML? Not needed. We'll produce:
About the role
We Are Accenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services—creating tangible value at speed and scale. We are a talent- and innovation-led company with approximately 790,000 people serving clients in more than 120 countries. Technology is at the core of change today, and we are one of the world’s leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability. Our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song, together with our culture of shared success and commitment to creating 360° value, enable us to help our clients reinvent and build trusted, lasting relationships. We measure our success by the 360° value we create for our clients, each other, our shareholders, partners and communities. Visit us at accenture.com. Our AI and Data practice sits at the intersection of deep industry knowledge and applied AI and data engineering. We help the world’s leading Resources and Utilities organizations reinvent how they run — designing the data foundations, AI platforms, and governance models that turn data into trusted, production-grade intelligence. We are not looking for generalists who advise on AI in the abstract. We need practitioners who understand how enterprises actually operate, where the friction lives, and how to engineer smarter solutions using AI and data to fundamentally transform business processes and outcomes.
Responsibilities
- Build AI applications — develop and integrate AI applications using leading model providers (OpenAI, Anthropic) and cloud platforms (AWS Bedrock, Azure OpenAI, Google Vertex AI).
- Implement LLM patterns — implement RAG, prompt orchestration, evaluation, and guardrails in LLM-powered applications, APIs, and pipelines.
- Deploy AI workloads — deploy and operationalize AI workloads on cloud infrastructure with scalability, security, cost efficiency, and reliability in mind.
- Engineer with modern tooling — use Python, API integration, vector databases, and orchestration frameworks (e.g., LangChain, LlamaIndex) to build production-ready solutions.
- Apply DevOps practices — apply containerization (Docker/Kubernetes), CI/CD, and cloud security best practices across the AI delivery lifecycle.
- Travel may be required for this role, varying from 0 to 80% depending on business need and client requirements.
Requirements
- Minimum of 3 years of experience in software or AI/ML/LLMs engineering.
- Minimum of 2 years of hands-on experience building AI applications with providers such as OpenAI, Anthropic, AWS Bedrock, Azure OpenAI, or Google Vertex AI.
- Minimum of 2 years of experience with Python and API integration.
- Minimum of 2 years of experience with RAG, vector databases, and orchestration frameworks (e.g., LangChain, LlamaIndex).
- Minimum of 1 year of experience with containerization (Docker/Kubernetes), CI/CD, and cloud security.
Qualifications
- Bachelor's degree in Computer Science/related field or equivalent (minimum 12 years' work experience). If Associate’s Degree, must have equivalent minimum 6-year work experience.
Skills
- Experience with leading model providers: OpenAI, Anthropic, AWS Bedrock, Azure OpenAI, Google Vertex AI.
- Proficiency in Python and API integration.
- Experience with RAG, vector databases, and orchestration frameworks (LangChain, LlamaIndex).
- Containerization and orchestration: Docker, Kubernetes.
- CI/CD pipelines and cloud security best practices.
- DevOps practices applied to AI delivery lifecycle.
- Experience with agentic AI patterns and multi-agent orchestration (bonus).
Benefits
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.
Pay
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 08/25/2026.
- 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: $63,80