AI Native Software Engineering Senior Manager Join to apply for the AI Native Software Engineering Senior Manager role at Accenture 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. 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. What You Need: Minimum of 10 years engineering experience with cloud-native systems (APIs, microservices, containerization, serverless). Minimum of 1 year of deep expertise in designing and deploying agentic solutions (agents, orchestration, context engineering, RAG, workflows) in production environments. Minimum of 7 years of experience with AI platforms — OpenAI, Claude, Vertex AI, plus open-source models — including building abstraction layers to manage multi-provider pipelines. Minimum of 10 years of experience programming in Python, Java, or equivalent; familiarity with evaluation tooling, logging, monitoring, and agent observability. Minimum of 10 years of experience deploying to production — CI/CD, infrastructure as code (Terraform, Helm), monitoring, and debugging. Minimum of 10 years of experience in client communication and collaboration, including being capable of leading technical workshops and delivering under ambiguity. Bachelor’s degree in Computer Science, Engineering, or equivalent; additional AI certifications or agentic tool experience is a plus. Bonus Points If: You’ve served as an Agentic AI Engineer in an Enterprise environment 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. Travel: Travel may be required for this role. The amount of travel will vary from 0 to 100% depending on business need and client requirements. Compensation and Benefits: Compensation at Accenture varies depending on a wide array of factors, including location, role, skill set, and experience. A reasonable range of compensation for roles in various locations is provided below as required by local law. Applications are accepted on an ongoing basis with no fixed deadline. Information on benefits is here. Role Location Annual Salary Range California $132,500 to $302,400 Colorado $132,500 to $261,300 District of Columbia $141,100 to $278,200 Illinois $122,700 to $261,300 Minnesota $132,500 to $261,300 Maryland $132,500 to $261,300 New York/New Jersey $122,700 to $302,400 Washington $141,100 to $278,200 Equal Employment Opportunity and Accommodation: Accenture is committed to providing equal employment opportunities for persons with disabilities or religious observances, including reasonable accommodation when needed. If you require accommodation to perform essential functions or during the recruiting process, please participate in our reasonable accommodation process. Details on requesting accommodations are available by contacting us. Accenture is an EEO and Affirmative Action Employer of Veterans/Individuals with Disabilities. Details on the Equal Opportunity Statement are available in our policy documents. Applicants for employment in the US must have work authorization that does not require sponsorship now or in the future. Candidates who are currently employed by a client of Accenture or an affiliated Accenture business may not be eligible for consideration. The Company will not discriminate against applicants who have inquired about or disclosed pay information in accordance with applicable laws. California residents: additional notifications apply. Please read Accenture’s Recruiting and Hiring Statement for more information on data processing during the recruiting process.

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