AI Native Software Engineering Manager

We need to output only HTML fragment, no /, no markdown fences. Use

for section headings: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We must include sections only when posting has real specific content. We need to extract content. The posting includes: - Intro: "We are: A forward-thinking services company..." That's about the company, could be "About the role"? Actually "About the role" maybe includes description of role. The posting includes "You are: An AI Native Engineer..." That's description of candidate. Also "The Work:" description of responsibilities. Then "Responsibilities:" list. Then "Here’s What You Need:" list of requirements. Then "Bonus Points If:" list of bonuses. Then compensation info: "Compensation at Accenture varies..." and then a table of salary ranges per location. Then benefits: "Accenture offers a market competitive suite of benefits..." Then location info? There's "Role Location Annual Salary Range" table. Also travel note: "Travel may be required for this role. The amount of travel will vary from 0 to 100% depending on business need and client requirements." That's schedule? Actually travel is not schedule but maybe schedule section? The schedule section is for work schedule (e.g., full-time, remote). Not present. So we may omit Schedule. Pay: we have salary ranges per location. That's specific content, so include Pay section. Benefits: we have description of benefits, include Benefits. Qualifications: The "Here’s What You Need:" is requirements. Could be Requirements or Qualifications. The instruction says use headings like Requirements, Qualifications, Skills. We need to decide which to use. Probably Requirements for mandatory qualifications, Qualifications for preferred? But we have both mandatory and bonus points. Could split: Requirements (mandatory), Qualifications (bonus). Or Skills for technical skills. Let's map: - About the role: description of company and role (We are..., You are..., The Work:). Could be About the role. - Responsibilities: list under "Responsibilities:" (Agent Architecture and Engineering, etc.) - Requirements: mandatory requirements from "Here’s What You Need:" (minimum years etc.) - Qualifications: maybe bonus points? Or could be Skills: list of technical skills (Python, Java, etc.) but those are within requirements. Better to have Requirements (mandatory) and Qualifications (bonus). Or Skills (technical). Let's decide: Use Requirements for mandatory, Qualifications for bonus points, Skills maybe not needed. But we need to follow instruction: "Use

for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule)." It says e.g., meaning we can choose among those. We should include sections that have real content. We have content for About the role, Responsibilities, Requirements (mandatory), Qualifications (bonus), Benefits, Pay. No Schedule. Skills maybe not separate; we could embed skills within Requirements. But we could also create Skills section for technical skills like Python, Java, containerization, etc. However those are already in requirements. To avoid duplication, better not to create Skills if it would be thin. The instruction: "Prefer a few substantive sections over many thin ones." So we likely combine. Thus sections: About the role, Responsibilities, Requirements, Qualifications, Benefits, Pay. Now we need to preserve all substantive information, not invent or summarize away detail. Must not repeat job title as heading. Must not put Job ID/requisition numbers as headings (none). Remove boilerplate: cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. So we need to strip out the EEO statements, accommodation request, equal employment opportunity statement, other employment statements, etc. Also remove lines like "Requesting an Accommodation", "Equal Employment Opportunity Statement", "Accenture is an EEO...", "Other Employment Statements", "Applicants for employment in the US must have work authorization...", etc. Also remove "See more information on our benefits here: U.S. Employee Benefits | Accenture". Also remove "Compensation at Accenture varies depending on a wide array of factors..."? That is part of Pay section, we keep. Also remove "As required by local law, Accenture provides a reasonable range of compensation for roles that may be hired as set forth below." That's part of Pay. Keep. Also remove "We anticipate this job posting will be posted until 10/16/2026." That's boilerplate? Might be considered metadata; but it's not a heading. Could be removed as it's not substantive about role. Probably remove. Also remove "Role Location Annual Salary Range" heading? That's part of Pay table; we can keep the table but not as heading. We'll embed the table inside Pay section maybe as

• or

  . But we need to preserve all substantive info: the salary ranges per location. Could present as

  • California: $94,400 to $316,300
  etc. Also benefits: list medical, dental, vision, life, long-term disability, 401(k), bonus opportunities, paid holidays, paid time off. Keep. Now we need to format. We'll produce:

  About the role

  We are a forward-thinking services company at the forefront of AI-native innovation. We partner with enterprise clients to create next-generation, agent-powered workflows engineered to scale in real-world settings. Our engineers embed deeply with customers, moving projects beyond experimentation into operational reality. You are an AI Native Engineer with a minimum of 5 years of experience building cloud-native solutions, and deep expertise in designing and deploying agentic systems, especially for enterprise environments. You are a critical thinker that thrives in ambiguity, delivering concrete results by designing, building, and running custom AI agents that augment workflows and scale across modern infrastructure. You’ll help shape the playbook for how enterprises adopt and scale AI-native engineering globally. The Work: You’ll embed directly with clients — acting as both technologist and trusted advisor. You’ll partner with stakeholders to define use cases, rapidly prototype, and deploy agentic workflows that are robust, secure, and operational in complex enterprise domains. Often, these will be completely net new platforms and systems that need to be stitched together in our clients' environments alongside our Ecosystem partners.

  But note: The text includes "The Work:" which is basically responsibilities; but we already have Responsibilities section. Might duplicate. However we should preserve all substantive info; we can incorporate the "The Work:" description into About the role or Responsibilities. To avoid duplication, maybe keep About the role as company description and candidate description, and keep Responsibilities separate for the bullet list. The "The Work:" paragraph is essentially a summary of responsibilities; we could keep it in About the role or Responsibilities. Since we have a detailed Responsibilities list, we could keep the brief description in About the role. Let's include it. Thus About the role includes company description, candidate description, and the Work summary. Now Responsibilities: list each bullet from "Responsibilities:" section. We need to use
  • for any list of duties/requirements/benefits. Thus:

    Responsibilities

    • Agent Architecture and Engineering: Design and engineer enterprise-ready AI agents encompassing retrieval, orchestration, policy-based routing, tool invocation, evaluation harnesses, and lifecycle observability.
    • AI Platform Integration: Develop abstraction layers across AI providers (Anthropic, Google, OpenAI, etc.) to enable seamless integration and enablement.
    • Cloud-Native Engineering: Leverage containerization (Kubernetes, Docker), microservices, serverless, event-driven architectures, CI/CD, and observability to deliver scalable AI-native systems.
    • Domain-Specific Workflows: Tailor and deploy agentic applications across verticals — e.g., finance, healthcare, retail — addressing domain-specific processes via intelligent automation.
    • Client Engagement: Conduct design workshops, POCs, and code-with sessions to shape data-driven agent workflows with stakeholders, fostering trust and adoption.
    • Measure & Improve: Define and use key metrics, test harnesses, and evaluation plans to measure agent accuracy, latency, safety, and cost effectiveness.
    • Knowledge Sharing: Craft reusable patterns, documentation, and best practices to influence internal assets and client roadmaps.
    • Travel may be required for this role. The amount of travel will vary from 0 to 100% depending on business need and client requirements.
    Note: Travel bullet is from after Responsibilities; we included. Now Requirements: from "Here’s What You Need:" list. We need to preserve all details: Minimum of 3 years engineering experience with cloud-native systems (APIs, microservices, containerization, serverless). Minimum of 1 year expertise in designing and deploying agentic solutions (agents, orchestration, context engineering, RAG, workflows) in production environments. Minimum of 2 years experience with AI platforms — OpenAI, Claude, Vertex AI, plus open-source models — including building abstraction layers to manage multi-provider pipelines. Minimum of 5 years experience programming in Python, Java, or equivalent; familiarity with evaluation tooling, logging, monitoring, and agent observability. Minimum of 5 years experience deploying to production — CI/CD, infrastructure as code (Terraform, Helm), monitoring, and debugging. Minimum of 5 years experience with client communication and collaboration, including being capable of leading technical workshops and delivering under ambiguity. Bachelor's degree or equivalent (minimum 12 years) work experience. (If Associate Degree, must have minimum 6 years work experience) We'll put each as
  • . Now Qualifications: from "Bonus Points If:" list. - You’ve served as an Agentic AI Engineer in an Enterprise environment - Additional AI certifications or agentic tool experience is a plus. - You’ve defined or worked with enterprise-grade architectures for compound AI systems, orchestration frameworks, or agent registry/stream-based architectures. - You understand the AI-native paradigm — blending cloud-native with generative model architectures — optimizing for performance, modularity, and efficiency. - You’ve delivered solutions across multiple industries (e.g., finance, healthcare) by tailoring agentic workflows to industry needs We'll put each as
  • . Now Benefits: from "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." We'll list each as
  • . Now Pay: from compensation table. We need to include all location salary ranges. List: - California: $94,400 to $316,300 - Cleveland: $87,400 to $253,000 - Colorado: $94,400 to $273,200 - District of Columbia: $100,500 to $291,000 - Illinois: $87,400 to $273,200 - Maine: $80,400 to $232,800 - Maryland: $94,400 to $273,200 - Massachusetts: $94,400 to $291,000 - Minnesota: $94,400 to $273,200 - New York: $87,400 to $316,300 - New Jersey: $100,500 to $316,300 - Virginia: $87,400 to $291,000 - Washington: $100,500 to $291,000 We'll put each as
  • . Now ensure we