Job Description
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.