AI Application Architect

Key Responsibilities: Work closely with customers and stakeholders to understand business problems and translate them into technology solutions. Design, generate and validate AI-generated code and engineering artifacts, and drive deployment of enterprise-grade applications, integrations, and AI-powered solutions. Apply prompt engineering, context engineering, and AI enablement techniques to improve solution outcomes. Review and validate AI-generated artifacts including requirements, design documents, code, and technical specifications. Review and validate AI-generated test designs, test cases, Playwright automation scripts, and quality engineering assets to ensure functional accuracy, adequate coverage, maintainability, and production readiness. Ensure compliance with enterprise security, governance, DevSecOps, and quality standards. Build and orchestrate agentic workflows, automation pipelines, and developer productivity solutions. Develop solution prototypes, proof-of-concepts, and production-ready implementations. Support customer engagements, workshops, demonstrations, and solution consulting activities.

Required Skills: Technical SkillsStrong software engineering background with 5–7 years of experience. Strong proficiency in Python, with the ability to review, validate, debug, and optimize AI-generated code for enterprise use. Experience leveraging AI-assisted development tools such as GitHub Copilot, Claude, Cursor, or equivalent platforms. Experience working with Spec-Driven Development methodologies. Hands-on experience with APIs, microservices, and modern application architectures. Familiarity with CI/CD, DevSecOps, automated testing, and deployment pipelines. Experience with test automation frameworks such as Playwright, Selenium, or equivalent. Professional SkillsStrong problem-solving and analytical capabilities. Customer-facing communication and consulting skills. Ability to work independently in fast-paced environments. Experience collaborating with cross-functional and distributed teams. Strong ownership mindset with a focus on measurable business outcomes.

Preferred Qualifications: Experience in Banking & Financial Services (BFS) domain. Exposure to Agentic SDLC, Spec-Driven Development, or AI-assisted delivery models. Understanding of cloud-native architectures and platform engineering.