Position Overview:

We are looking for a hands-on Lead Solution Architect - Innovation & Emerging Technologies who can bridge the gap between rapid technology experimentation and enterprise-scale implementation.

The role involves providing architectural and engineering leadership across PoCs, prototypes, and Minimum Viable Products (MVPs), ensuring promising solutions have a clear and practical pathway to production. The candidate will mentor developers, establish reusable engineering practices, and strengthen the team's architecture and production engineering capabilities.

Key Responsibilities:

- Lead solution architecture for Innovation Hub PoCs, prototypes, and MVPs, ensuring scalability and production readiness.

- Work hands-on with developers to resolve complex engineering challenges across applications, cloud, integrations, data, and AI.

- Design secure, scalable, resilient, maintainable, observable, and cost-effective technology solutions.

- Provide architectural leadership for AI/ML, Generative AI, RAG, and Agentic AI solutions.

- Guide cloud-native architecture, including APIs, microservices, containers, serverless technologies, CI/CD, Infrastructure as Code (IaC), and DevSecOps.

- Incorporate production engineering considerations early to minimize technical debt and avoid unnecessary re-engineering.

- Collaborate with Enterprise Architecture, Cloud/Platform Engineering, Security, Privacy, Risk, and Delivery teams to align solutions with enterprise standards.

- Establish reference architectures, reusable components, technical standards, and engineering patterns across PoCs and MVPs.

- Evaluate emerging technologies, platforms, and startup solutions for enterprise applicability, feasibility, and business value.

- Mentor developers through architecture and design reviews, pair programming, code reviews, and technical coaching.

- Ensure smooth knowledge transfer and transition of successful Innovation Hub solutions to enterprise delivery teams.

Required Experience & Skills:

- 10+ years of technology experience, with strong expertise in solution, application, or cloud architecture.

- Strong software engineering fundamentals with hands-on development experience.

- Proven experience taking solutions from prototype/MVP through enterprise production.

- Strong knowledge of cloud-native architectures, preferably AWS and/or Azure.

- Hands-on experience with APIs, microservices, distributed systems, containers/Kubernetes, and modern integration patterns.

- Strong understanding of CI/CD, DevSecOps, Infrastructure as Code, application security, and observability.

- Practical knowledge of AI/ML and Generative AI architecture.

- Experience with LLMs, RAG, AI Agents/Agentic AI, vector databases, AI guardrails, or related AI architecture patterns is highly desirable.

- Understanding of enterprise security, privacy, risk, and architecture governance.

- Demonstrated ability to mentor developers and improve engineering practices.

- Excellent communication skills, with the ability to translate complex technology decisions into clear business terms.

Technical Skills:

- Cloud & Infrastructure: AWS, Azure, Kubernetes, Docker, Serverless

- AI & Emerging Technologies: Generative AI, LLMs, RAG, Agentic AI, MCP, Vector Databases, AI Guardrails

- Development: Python, Java, JavaScript/TypeScript, React/Next.js, APIs

- Engineering & DevSecOps: CI/CD, GitHub, Infrastructure as Code (IaC), automated testing, security scanning