Agentic AI Architect

Job Description - Grade Specific We are looking for a highly experienced Agentic AI Architect to lead the design and implementation of enterprise-scale agentic AI solutions. This role will be responsible for defining architecture, guiding development teams, and ensuring scalable, secure, and high-performing AI systems that leverage LLMs, multi-agent frameworks, and enterprise integrations. The ideal candidate combines deep technical expertise in AI/ML with strong architectural design skills and experience delivering complex, production-grade AI solutions. Key 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, CrewAI, etc. Lead development of LLM-driven systems (Azure OpenAI, OpenAI, Anthropic, etc.) 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 (CRM, ERP, APIs, 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 Drive innovation by evaluating emerging AI technologies and frameworks Required Skills & Experience 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 - Embeddings and vector databases (FAISS, Pinecone, Azure AI Search, etc.) - Retrieval-Augmented Generation (RAG) Experience with cloud platforms (Azure preferred, AWS/GCP 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 Good to Have Experience with Model Context Protocol (MCP) or similar integration standards Exposure to enterprise AI transformation programs Knowledge of MLOps / LLMOps frameworks Experience with frontend or conversational UI frameworks Certifications (Azure AI Engineer, Solutions Architect, etc.)' The base compensation range for this role in the posted location is: $125000/yr- $140000/Yr Capgemini provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws. The base compensation range listed for this position reflects the minimum and maximum target compensation Capgemini, in good faith, believes it may pay for the role at the time of this posting. This range may be subject to change as permitted by law. The actual compensation offered to any candidate may fall outside of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction. These may include, but are not limited to: Geographic location, Education and qualifications, Certifications and licenses, Relevant experience and skills, Seniority and performance, Market and business consideration, Internal pay equity. It is not typical for candidates to be hired at or near the top of the posted compensation range. In addition to base salary, this role may be eligible for additional compensation such as variable incentives, bonuses, or commissions, depending on the position and applicable laws. Capgemini offers a comprehensive, non-negotiable benefits package to all regular, full-time employees. In the U.S. and Canada, available benefits are determined by local policy and eligibility and may include: Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade, Company paid holidays, Personal Days, Sick Leave Medical, dental, and vision coverage (or provincial healthcare coordination in Canada) Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada) Life and disability insurance Employee assistance programs Other benefits as provided by local policy and eligibility