AI Architect

Requirements

• 8 years of experience with AI systems and Agentic systems
• 4 years experience with AI and/or Data
• Experience with Python, agent frameworks, data engineering, APIs/microservices, vector databases, SQL engines, distributed systems, cloud services, RAG
• Understanding of DevOps tools and principals
• Experience with Model Context Protocol
• Bachelors degree
• Security Clearance:
• Active TS/SCI with polygraph clearance
• The pay range for the states of California, Colorado, Hawaii, Illinois, Maryland, Massachusetts, Minnesota, New Jersey, New York, Washington, Vermont, the District of Columbia, and the city of Cleveland is:
• $130,200 - $265,300 USD
• What We Believe
• Equal Employment Opportunity Statement
• Accenture Federal Services is an Equal Employment Opportunity employer. Additionally, as an Affirmative Action Employer for Veterans and Individuals with Disabilities, Accenture Federal Services is committed to providing veteran employment opportunities to our service men and women.
• Requesting An Accommodation
• Accenture Federal Services is committe

Benefits

Additional Information

At Accenture Federal Services, nothing matters more than helping the US federal government make the nation stronger and safer and life better for people. Our 13,000+ people are united in a shared purpose to pursue the limitless potential of technology and ingenuity for clients across defense, national security, public safety, civilian, and military health organizations. Join Accenture Federal Services, a technology company within global Accenture. Recognized as a Glassdoor Top 100 Best Place to Work, we offer a collaborative and caring community where you feel like you belong and are empowered to grow, learn and thrive through hands-on experience, certifications, industry training and more. Join us to drive positive, lasting change that moves missions and the government forward! Lead the end-to-end technical design, development, and implementation of an agentic AI system to orchestrate user queries across heterogeneous data sources. The architect is responsible for defining the overall system architecture, selecting and governing AI/ML and platform technologies, and ensuring the solution is scalable, secure, and production-ready. The architect partners closely with development, DevOps and data engineering teams to translate project requirements into an extensible AI architecture. Must have experience designing and deploying LLM-based systems, including RAG, tool-calling, and multi-agent patterns, as well as a strong understanding of modern AI architectures such as embeddings, vector search, orchestration layers, memory, and reasoning workflows. Proven ability to evaluate models, manage prompt strategies, and design system for traceability and reliability.

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