AI Native Software Engineering Senior Manager/Assoc Director

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.

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.

Requirements

• Minimum of 10 years engineering experience with cloud-native systems (APIs, microservices, containerization, serverless).
• Minimum of 1 years 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.

Qualifications

• 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.

Skills

• Experience with Anthropic, Google, OpenAI, and other AI providers.
• Familiarity with evaluation tooling, logging, monitoring, and agent observability.
• Expertise in cloud-native technologies such as Kubernetes, Docker, and serverless.
• Strong experience in Python, Java, or equivalent programming languages.
• Ability to lead technical workshops and collaborate with stakeholders.

Benefits

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.

Pay

Annual Salary Range: Varies by location.

Schedule

Variates based on business need and client requirements.