Principle Solution Architect

Key Responsibilities

• Analyze legacy applications to uncover business rules, data flows, and cross-system dependencies using a mix of expertise and AI agent support.
• Architect future-state solutions with a focus on microservices, event-driven patterns, and cloud-native deployments.
• Build and orchestrate custom AI-powered agent workflows within rapidX to automate reverse engineering, rule extraction, blueprinting, and modernization tasks.
• Develop playbooks and reusable modernization frameworks, scaling the role of intelligent agents and automation into standard practice.
• Act as the lead architect for early customer projects, shaping both the modernization strategy and the use of agentic tooling as an accelerator.
• Mentor and grow a team of architects who can drive modernization using a combination of expertise, rapidX, and purpose-built AI workflows.
• Work with product teams to recommend enhancements to rapidXs agent ecosystem based on real-world architectural insights and customer feedback.

Required Skills and Qualifications

• 15+ years of total IT experience, including hands-on solution architecture and engineering.
• Proven expertise in designing enterprise-grade, cloud-native, cloud-agnostic, and hybrid applications.
• Strong understanding of Azure / AWS / GCP platforms, including distributed design, networking, security, and deployment patterns.
• Experience with microservices, event-driven architecture, designing message-based systems, and data modeling for scalable, decoupled systems.
• Solid grounding in API-first development, REST, authentication (OAuth), and integration patterns with modern AI platforms and APIs.
• Experience with containers and orchestration (Docker, Kubernetes).
• Familiarity with observability ecosystems such as Prometheus, ELK, Grafana, Azure Monitor, etc.
• Ability to analyze and understand complex systems and codebases to develop modernization would-be blueprints.
• Strong stakeholder engagement skills with the ability to guide technical and business teams through complex transformations.

Preferred / Nice-to-Have Skills

• Experience designing or orchestrating AI agents or agentic workflows for engineering or automation use cases.
• Exposure to graph databases (Neo4j, Gremlin) for system mapping or knowledge modeling.
• Background in AI-assisted development, intelligent automation, or code analysis using GenAI tools.
• Understanding of domain-driven design, event streaming, and modern data architectures.
• Awareness of zero-trust security principles in cloud or distributed systems.

What We Offer

• A chance to shape the future of modernization using AI — not just talk about it.
• Work on high-impact programs where AI agents and intelligent automation deliver business outcomes at scale.
• A collaborative environment with freedom to experiment, learn, and create modernization IP assets.
• Continuous exposure to emerging architectural models, applied AI, and cloud-native engineering.