Full Stack Forward Deployed Engineering Manager

Accenture•St. Louis, MO

9d•$80,400 - $316,300

About The Position

Accenture is hiring a Full Stack Forward Deployed Engineering Manager to help enterprise clients design, build, and operationalize AI-native, agent-powered workflows. The role embeds with clients as both a technologist and trusted advisor, partnering with stakeholders to define use cases, prototype solutions, and deploy robust and secure agentic workflows in complex enterprise environments. Work may involve creating new platforms and integrating systems within client environments alongside ecosystem partners. The position focuses on engineering enterprise-ready AI agents and cloud-native systems, integrating multiple AI providers, adapting workflows to industry-specific processes, and measuring and improving agent performance. The role also contributes reusable patterns, documentation, and best practices to internal assets and client roadmaps. Travel may range from 0% to 100%, depending on business needs and client requirements.

Requirements

At least 3 years of engineering experience with cloud-native systems, including APIs, microservices, containerization, and serverless.
At least 1 year of experience designing and deploying production agentic solutions, including agents, orchestration, context engineering, RAG, or workflows.
At least 2 years of experience with AI platforms such as OpenAI, Claude, Vertex AI, and open-source models, including building abstraction layers for multi-provider pipelines.
At least 5 years of programming experience in Python, Java, or an equivalent language; familiarity with evaluation tooling, logging, monitoring, and agent observability.
At least 5 years of experience deploying to production, including CI/CD, infrastructure as code such as Terraform or Helm, monitoring, and debugging.
At least 5 years of experience in client communication and collaboration, including the ability to lead technical workshops and deliver under ambiguity.
Bachelor's degree or equivalent, with a minimum of 12 years of work experience; alternatively, an associate degree with a minimum of 6 years of work experience.
For U.S. employment, work authorization that does not now or in the future require visa sponsorship.

Nice To Haves

Experience serving as an Agentic AI Engineer in an enterprise environment.
Additional AI certifications or experience with agentic tools.
Experience defining or working with enterprise-grade architectures for compound AI systems, orchestration frameworks, or agent registry/stream-based architectures.
Understanding of the AI-native paradigm, combining cloud-native and generative model architectures while optimizing performance, modularity, and efficiency.
Experience delivering solutions across multiple industries by tailoring agentic workflows to industry needs.

Responsibilities

Design and engineer enterprise-ready AI agents, including retrieval, orchestration, policy-based routing, tool invocation, evaluation harnesses, and lifecycle observability.
Develop abstraction layers across AI providers such as Anthropic, Google, and OpenAI.
Build scalable AI-native systems using containerization, microservices, serverless and event-driven architectures, CI/CD, and observability.
Tailor and deploy agentic applications for industry-specific workflows, including finance, healthcare, and retail.
Conduct design workshops, proofs of concept, and code-with sessions with client stakeholders to shape data-driven agent workflows and foster trust and adoption.
Define and use metrics, test harnesses, and evaluation plans to measure agent accuracy, latency, safety, and cost effectiveness.
Create reusable patterns, documentation, and best practices that influence internal assets and client roadmaps.
Travel as required by business needs and client requirements; travel may range from 0% to 100%.