AI Native Software Engineering Manager
Accenture · Arlington, VA · 3 wk ago
HybridEngineering$94k–$305k/yrFull-time
About the role
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 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 3 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)
Qualifications
- 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
Skills
- Experience with Anthropic, Google, OpenAI, and open-source models
- Familiarity with evaluation tooling, logging, monitoring, and agent observability
- Experience with CI/CD, Terraform, Helm, and infrastructure as code
- Ability to lead technical workshops and deliver under ambiguity
- Understanding of AI-native paradigm and compound AI systems
- Experience delivering solutions across multiple industries
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 based on location and experience
Schedule
Variation in travel required, ranging from 25% to 75%