Agentic AI Architect

Capgemini • Atlanta, GA

3d • $125,000 - $140,000

About The Position

Capgemini is seeking a highly experienced Agentic AI Architect to lead the design and implementation of enterprise-scale agentic AI solutions. The role defines architecture, guides development teams, and ensures that AI systems leveraging LLMs, multi-agent frameworks, and enterprise integrations are scalable, secure, and high-performing. The position combines deep AI/ML expertise with architectural design skills and experience delivering complex, production-grade AI solutions.

The architect defines end-to-end architecture for agentic AI solutions, designs and implements agent frameworks, leads development of LLM-driven systems, and architects RAG pipelines, memory systems, and tool-integration layers. The role establishes AI governance, security, and Responsible AI practices; designs integrations with enterprise systems; and provides technical leadership and mentorship. It also partners with business stakeholders to translate requirements into technical solutions, optimizes system performance and cost, and evaluates emerging AI technologies and frameworks.

The posted base compensation range is $125,000–$140,000 per year. The role may also be eligible for variable incentives, bonuses, or commissions. Capgemini states that regular, full-time employees may receive benefits subject to local policy and eligibility, including paid time off, company holidays, personal days, sick leave, medical, dental and vision coverage, retirement savings plans, life and disability insurance, and employee assistance programs.

Requirements

• 10+ years of experience in software engineering, AI/ML, or solution architecture.
• Strong expertise in Python and modern backend architectures.
• Hands-on experience with LLM ecosystems and agent frameworks.
• Proven experience designing multi-agent systems and distributed architectures.
• Deep understanding of prompt engineering and LLM optimization.
• Experience with embeddings and vector databases such as FAISS, Pinecone, or Azure AI Search.
• Experience with Retrieval-Augmented Generation (RAG).
• Experience with cloud platforms; Azure is preferred, while AWS or GCP is acceptable.
• Strong knowledge of API design, microservices, and event-driven architecture.
• Familiarity with security, authentication (OAuth, SSO), and data governance.
• Experience leading technical teams and driving architecture decisions.

Nice To Haves

• Experience with Model Context Protocol (MCP) or similar integration standards.
• Exposure to enterprise AI transformation programs.
• Knowledge of MLOps or LLMOps frameworks.
• Experience with frontend or conversational UI frameworks.
• Certifications such as Azure AI Engineer or Solutions Architect.

Responsibilities

• Define end-to-end architecture for agentic AI solutions, including multi-agent systems, orchestration layers, and integrations.
• Design and implement scalable agent frameworks using technologies such as LangChain, Semantic Kernel, AutoGen, and CrewAI.
• Lead development of LLM-driven systems using platforms such as Azure OpenAI, OpenAI, and Anthropic, with robust prompting strategies.
• Architect RAG pipelines, memory systems, and tool-integration layers.
• Establish best practices for AI governance, security, and Responsible AI.
• Design integration strategies with enterprise systems, including CRM, ERP, APIs, and data platforms.
• Provide technical leadership, mentorship, and code-quality oversight to development teams.
• Collaborate with business stakeholders to translate requirements into technical solutions.
• Ensure performance, scalability, reliability, and cost optimization of AI systems.
• Evaluate emerging AI technologies and frameworks to drive innovation.

Benefits

• Paid time off based on employee grade, including 12–25 vacation days depending on grade, company-paid holidays, personal days, and sick leave.
• Medical, dental, and vision coverage, or provincial healthcare coordination in Canada.
• Retirement savings plans, such as a 401(k) in the U.S. or RRSP in Canada.
• Life and disability insurance.
• Employee assistance programs.
• Other benefits as provided by local policy and eligibility.
• The role may be eligible for variable incentives, bonuses, or commissions, depending on position and applicable laws.

What This Job Offers

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