Forward Deployed Engineer Manager

Accenture•St. Louis, MO

6d•$80,400 - $316,300•Hybrid

About The Position

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. This is a product-minded, customer-embedded engineering role where you will work directly with clients, partners, and internal product teams to design, prototype, deploy, and scale end-to-end AI solutions. You will work hands-on with platforms such as OpenAI, Anthropic, Google Gemini, SAP, ServiceNow, and other enterprise systems, translating ambiguous business needs into production-grade AI workflows that deliver measurable impact. This role requires strong engineering depth, excellent communication, comfort with ambiguity, and a builder’s mindset.

Requirements

5+ years software engineering experience (Python, TypeScript/JavaScript, Java) with 5 years’ experience integrating APIs and building distributed, production systems.
2+ years experience with modern AI/ML platforms such as: OpenAI, Anthropic, or similar foundation model providers, Workflow orchestration and agent frameworks.
5+ years experience translating high-level business needs into concrete technical designs and implementations in a large enterprise-wide organizations or professional services firm.
5+ years enterprise platforms (ServiceNow, Salesforce, SAP, data platforms, etc.)
5+ years of experience in client-facing communication and collaboration, including leading technical discussions, workshops, or delivery sessions under ambiguity.
Bachelor's degree in Computer Science, Engineering or equivalent OR equivalent (minimum 12 years) work experience. (If Associate’s Degree, must have minimum 6 years work experience)

Responsibilities

Work directly with clients and internal teams to understand business problems, shape AI use cases, and define technical solutions — often from ambiguous or evolving requirements.
Design and implement end-to-end AI solutions, integrating LLMs and AI services (OpenAI, Anthropic, Gemini, etc.) with enterprise platforms (SAP, ServiceNow, Salesforce, data platforms, internal systems).
Rapidly prototype, iterate, and deploy AI-enabled workflows, agents, copilots, and automations into real operational environments.
Serve as the technical bridge between product, engineering, data, and business stakeholders, ensuring solutions are technically sound, usable, and aligned with business value.
Drive solution architecture, including: Prompt and workflow design, API integrations and orchestration, Enterprise knowledge integration, Security, privacy, and governance considerations.
Own solutions from concept → prototype → production → iteration, with accountability for quality, reliability, and outcomes.
Provide technical leadership and best practices for responsible, secure, and scalable AI deployment.