AI Architect

Role: AI Tech Lead

Location: Washington, DC 20433

Duration: 6 Months – Long Term

Hybrid Onsite: 4 days per week from Day 1, with a full transition to 100% onsite anticipated soon

Background:

The organization is seeking an experienced Applied AI Engineering Lead to drive the design, development, and implementation of enterprise-scale Agentic AI solutions. The role will lead the adoption of Large Language Models (LLMs), multi-agent systems, intelligent automation, and cloud-native AI architectures to modernize business processes, accelerate knowledge management, enhance incident management capabilities, and improve operational efficiency.

Scope of Work

AI Strategy & Solution Architecture

• Design enterprise AI architectures leveraging LLMs, Agentic AI frameworks, Retrieval-Augmented Generation (RAG), MCP Servers, Semantic Kernel, and multi-agent orchestration platforms.
• Define AI solution patterns, technical standards, and governance frameworks.
• Develop scalable, secure, and responsible AI architectures aligned with enterprise policies.

Agentic AI Solution Development

• Design and implement autonomous AI agents capable of planning, reasoning, orchestrating tasks, and interacting with enterprise systems.
• Build intelligent workflows for incident management, document processing, knowledge management, customer support, and operational automation.
• Develop prompt engineering, context engineering, memory management, and orchestration strategies to optimize AI performance.

Cloud & DevOps Enablement

• Architect and deploy AI solutions on cloud platforms such as Microsoft Azure.
• Implement CI/CD pipelines, infrastructure-as-code, monitoring, observability, and AI operations (AIOps) capabilities.
• Optimize cloud resources for performance, scalability, and cost efficiency.

Leadership & Capacity Building

• Lead multidisciplinary engineering teams across onshore and offshore locations.
• Mentor engineers and architects in Agentic AI patterns, cloud-native engineering, and modern software development practices.
• Establish communities of practice and standards for AI engineering excellence.

Required Qualifications

• Master's degree in Computer Science, Information Technology, Data Science, Artificial Intelligence, Engineering, or related discipline.
• Minimum 10 years of professional experience in software engineering and enterprise solution delivery.
• Minimum 5 years of experience in cloud architecture and modern application development.
• Demonstrated experience delivering AI/ML and Generative AI solutions in large enterprises.
• Proven experience leading cross-functional engineering teams.
• Experience delivering solutions using Agile and Scrum methodologies.

“Mindlance is an Equal Opportunity Employer and does not discriminate in employment on the basis of – Minority/Gender/Disability/Religion/LGBTQI/Age/Veterans.”