Your RoleAs an
AI Solution Architect, you will lead the design, architecture, and delivery of enterprise AI solutions with a focus on
agentic AI systems built on Azure AI Foundry. You will combine strategic architecture leadership with hands-on engineering, translating business requirements into scalable, secure, and production-ready AI solutions.
You will be responsible for the end-to-end solution architecture, including agent design, orchestration patterns, system decomposition, integration boundaries, and non-functional requirements. Working closely with product, engineering, data, and cloud teams, you will establish architecture standards, facilitate design reviews, and ensure alignment between business objectives and technical implementation.
This is a hands-on role requiring direct experience designing, developing, testing, and deploying AI agents and multi-agent workflows using
Python and Azure AI Foundry. You will build prototypes, proofs of concept, and reference implementations, as well as deliver executive and technical demonstrations that showcase solution value and validate architecture decisions.
Your Skills & Experience - 10+ years of experience in Solution Architecture.
- 2+ years of experience designing and delivering Generative AI, AI-powered, or agent-based solutions in production.
- Proven experience architecting and implementing multi-agent systems, AI copilots, or agentic workflows.
- Hands-on experience developing AI agents and orchestration workflows using Azure AI Foundry and Python.
- Experience building end-to-end agentic solutions, including tool calling, workflow orchestration, RAG, memory management, and enterprise integrations.
- Ability to translate architecture designs into working prototypes and production-ready implementations.
- Proven experience creating customer-facing demos, proofs of concept (POCs), and reference implementations that demonstrate business value and technical feasibility.
- Strong understanding of LLMs, prompt engineering, RAG architectures, AI evaluation frameworks, and Responsible AI principles.
- Experience designing cloud-native solutions on Microsoft Azure.
- Strong knowledge of APIs, microservices, integration patterns, and enterprise architecture best practices.
- Experience defining non-functional requirements, including security, scalability, performance, reliability, compliance, and data residency.
- Excellent communication, stakeholder management, documentation, and technical leadership skills.
Preferred - Experience delivering AI solutions in regulated or complex industries such as manufacturing, aerospace, industrial distribution, supply chain, healthcare, or financial services.
- Experience with Azure OpenAI, Azure AI Search, Microsoft Fabric, Snowflake, Databricks, and enterprise data platforms.
- Experience with vector databases and retrieval platforms such as Azure AI Search, Snowflake Cortex Vector Search, Pinecone, Weaviate, or pgvector.
- Familiarity with Semantic Kernel, LangChain, LangGraph, AutoGen, or similar agent orchestration frameworks.
- Experience with Docker, Kubernetes, GitHub, CI/CD pipelines, and modern software engineering practices.
- Knowledge of Responsible AI governance, model monitoring, observability, and enterprise AI adoption frameworks.
- Experience mentoring engineering teams and establishing AI architecture standards and best practices.
- Azure certifications such as Azure Solutions Architect Expert, Azure AI Engineer Associate, or equivalent.
Key Technologies: Azure AI Foundry, Azure OpenAI, Python, Azure AI Search, Microsoft Agent framework, Azure cloud, GitHub, REST APIs, and CI/CD platforms.
The base compensation range for this role in the posted location is: $180,000-$205,000
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
