AI Solution Architect
Summary
AMINA Bank's India subsidiary seeks an AI Solution Architect to lead the technology side of an AI squad building process automation and agentic-AI solutions for a regulated banking environment. The role designs LLM/RAG-driven workflows, APIs, and integrations on Microsoft Azure, and contributes hands-on from concept to production.
- Act as the technology lead and solution design owner for AI and automation initiatives.
- Partner closely with the Process Engineers to translate process improvement opportunities into feasible technology solutions.
- Challenge assumptions and ensure that AI is applied only where it creates real value — not as a default solution.
- Help shape the squad’s technical roadmap, delivery approach, and reusable solution patterns.
- Provide technical guidance to AI engineers, full-stack engineers, and other contributors.
- Design end-to-end solutions combining AI models, agentic workflows, APIs, business applications, data sources, and user interfaces.
- Define when to use AI, workflow automation, rule-based automation, data-driven solutions, or traditional software engineering.
- Design agentic AI patterns, retrieval-augmented generation flows, prompt orchestration, tool use, memory handling, and human-in-the-loop controls.
- Ensure AI solutions are explainable, traceable, reliable, and suitable for a regulated banking environment.
- Define guardrails, validation mechanisms, fallback paths, monitoring, and escalation points.
- Work with process engineers to understand current-state processes, target-state designs, pain points, bottlenecks, and automation potential.
- Translate business and process requirements into solution concepts, architecture decisions, and technical delivery plans.
- Support prioritization of use cases based on feasibility, value, complexity, risk, and reusability.
- Ensure solutions are not built on top of broken processes, but support a disciplined approach to simplification, standardization, and automation.
- Support AI / full-stack engineers in building backend services, frontend interfaces, APIs, integrations, and AI-enabled workflows.
- Review technical designs, integration patterns, and implementation choices.
- Contribute hands-on where needed, especially in early solution design, prototypes, technical spikes, and complex integrations.
- Ensure solutions follow sound software engineering practices, including testing, secure design, CI/CD, monitoring, and operational support.
- Design solutions using Microsoft Azure, Azure AI Foundry, Entra ID, Microsoft 365, SharePoint, and related enterprise platforms where appropriate.
- Ensure alignment with internal AI governance, security, data protection, software development, change management, and audit expectations.
- Collaborate with Security, SRE, Data Engineering, Legal, Compliance, and Data Protection teams where required.
- Support documentation of architecture decisions, risks, controls, and operational responsibilities.
- Stay current with fast-moving developments in AI, agentic systems, automation tools, and engineering practices.
- Evaluate new AI capabilities, frameworks, orchestration tools, and architectural patterns pragmatically.
- Help build reusable standards, templates, reference architectures, and engineering practices for AI and automation delivery.
- Coach others on responsible, effective, and practical use of AI technologies.
- Strong technical background in software engineering, solution architecture, AI engineering, automation, or cloud-based application delivery.
- Practical understanding of AI solution design, including large language models, prompt engineering, RAG, agents, tool use, model limitations, and evaluation approaches.
- Experience designing systems that integrate with APIs, data sources, enterprise platforms, workflow tools, and business applications.
- Good understanding of cloud architecture, preferably Microsoft Azure.
- Ability to design secure, scalable, maintainable, and production-ready solutions.
- Strong conceptual thinking combined with the ability to get into technical detail.
- Experience working with cross-functional teams across business, process, engineering, security, and operations.
- Ability to explain complex technical concepts clearly to both technical and non-technical stakeholders.
- Experience with process automation, workflow orchestration, or business process transformation.
- Familiarity with process engineering concepts such as Lean, Six Sigma, BPMN, process mining, or value-stream thinking.
- Hands-on exposure to AI agents, orchestration frameworks, RAG pipelines, Azure AI Foundry, Semantic Kernel, LangChain, n8n, Power Automate, or similar tools.
- Full-stack engineering understanding, including backend services, frontend applications, APIs, databases, and integration patterns.
- Experience in banking, fintech, financial services, or another regulated environment.
- Familiarity with auditability, traceability, human oversight, access control, logging, and operational resilience requirements.
- Proactive leader, not just a technical expert waiting for requirements.
- Strong sparring partner for process engineering and business stakeholders.
- Curious, hands-on, and motivated to continuously learn as AI evolves.
- Pragmatic: able to distinguish between what is technically impressive and what creates real business value.
- Comfortable working in ambiguity and shaping structure where none exists yet.
- Strong ownership mindset from concept through production delivery.
- Able to balance innovation, speed, security, governance, and maintainability.
