AI Solution Engineer

Accenture • Atlanta, GA

1d • Onsite

About The Position

Accenture is partnering with a leading global AI company to help small and mid-sized businesses turn generative AI opportunities into working solutions. As an AI Solution Engineer, you will work at the front line of that growth: engaging customers, understanding their business and technical needs, and shaping practical AI solutions they can integrate, validate and deploy. You will support multiple customer opportunities at pace, working alongside sales and a broader solution engineering team from discovery through technical validation and early onboarding. The role combines consultative client engagement with hands-on solution design. It will suit someone who enjoys explaining complex technology, prototyping ideas and helping customers move from interest in AI to confident adoption.

Requirements

• Minimum of 3 years of experience in solutions consulting, sales engineering, solution architecture, or technical account management.

Nice To Haves

• Hands-on experience building, configuring or evaluating generative AI solutions through enterprise work, pre-sales prototypes or personal projects.
• Practical knowledge of one or more leading AI platforms and assistants, such as ChatGPT, Claude, Gemini or Microsoft Copilot.
• Working knowledge of LLM APIs, prompt design, structured outputs, tool or function calling, retrieval-augmented generation, embeddings and retrieval techniques.
• Experience designing AI solutions that connect securely with enterprise applications, data sources and existing business processes.
• Understanding of where LLM-based applications perform well, their common limitations, and how grounding, evaluation and human oversight can improve solution quality.
• Ability to explain AI concepts and architectural choices to technical and non-technical stakeholders.
• Experience designing or prototyping agentic workflows, including the use of tools, connectors or agent frameworks.
• Familiarity with emerging integration standards such as Model Context Protocol.
• Experience with AI evaluation, guardrails, monitoring or observability.
• Strong understanding of API concepts, including RESTful design, authentication patterns, integration workflow design, and common error-handling practices.
• Familiarity with scripting, JSON payloads, or light troubleshooting (not a full coding role, but technical literacy expected).
• Knowledge of SOC2, ISO 27001, GDPR, and enterprise security standards.
• Background working with SMBs or high-velocity sales teams.

Responsibilities

• Partner with sales teams throughout the customer journey, leading technical discovery and clarifying the customer’s business context, workflows, technology landscape, data, security requirements and integration dependencies.
• Translate customer needs into practical solution designs using large language models, APIs, retrieval-augmented generation, tool calling, agentic workflows and connections to enterprise systems.
• Recommend appropriate architecture patterns, configuration options and implementation approaches.
• Advise customers on API integration, including authentication, rate limits, endpoints, performance considerations and data-flow design.
• Help customers identify where LLM-based solutions are a strong fit and where conventional software or automation may be more appropriate.
• Explain design trade-offs involving accuracy, grounding, security, privacy, latency, cost and operational support.
• Develop demonstrations that test customer use cases and show a credible path to implementation.
• Lead conversations around security posture, including data handling, encryption, authentication, access control, and compliance standards.
• Respond to customer security questionnaires and assist with risk assessments, with support from internal security teams as needed.
• Communicate how the platform aligns with enterprise-grade security practices and regulatory requirements.
• Partner with sales, product, and engineering to shape solution proposals that align with technical feasibility and customer value.
• Document recommended architectures, configuration steps, and onboarding plans.
• Identify potential technical blockers early and provide mitigation strategies.
• Work closely with Product and Engineering teams to escalate technical issues, influence roadmap, and share customer insights.
• Support Customer Success teams during the early post-sale phase to ensure smooth technical handoff and implementation readiness.
• Contribute to internal knowledge bases, FAQs, and solution playbooks to scale repeatable technical motions.

Benefits

• medical, dental, vision, life, and long-term disability coverage
• a 401(k) plan
• bonus opportunities
• paid holidays
• paid time off

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed