Solutions Architect

About the Company

Incedo is a global AI and data transformation specialist empowering companies to realize sustainable business impact from their digital investments by delivering ROI from AI@Scale. As a long-term partner for strategy to execution, we operate at the intersection of business and technology. Our integrated services and platforms are built on the foundation of AI & Data, digital engineering, and operations transformation, bringing deep domain expertise and full stack capabilities together. With over 4,000 people across the US, Canada, Latin America and India, and a large, diverse portfolio of Fortune 500 enterprises and fast-growing clients worldwide, we work across banking & payments, wealth management, telecom, hi-tech and life sciences.

About the Role

We are seeking a Solution Architect to define end-to-end architecture for AI-powered enterprise products. The ideal candidate should have extensive experience building scalable distributed systems, cloud-native platforms, and AI-enabled enterprise solutions.

Key Responsibilities

• Define overall technical architecture for enterprise applications.
• Design scalable, secure, and distributed systems.
• Create solution blueprints covering applications, APIs, databases, security, and infrastructure.
• Collaborate with engineering teams to ensure architectural compliance.
• Drive technology evaluations and proof of concepts.
• Define integration patterns with enterprise platforms.
• Lead architecture governance and technical reviews.
• Work closely with Product and Engineering leadership.

Qualifications

• 10+ years of software engineering experience.
• 5+ years in Solution Architecture.

Required Skills

• Expertise in microservices architecture.
• Experience designing large-scale distributed systems.
• Strong understanding of Cloud Architecture (Azure/AWS/GCP).
• Experience with containerization and Kubernetes.
• Strong API integration expertise.
• Knowledge of DevSecOps practices.
• Experience architecting AI-powered enterprise applications.
• Hands-on exposure to LLMs, RAG, AI Agents, and GenAI platforms.
• Experience with AI orchestration frameworks.
• Knowledge of Vector Databases and AI infrastructure.
• TOGAF or cloud certifications preferred.