AI Solutions Architect

Jeen is looking for a hands-on Enterprise AI Solutions Architect to own the technical design and delivery of end-to-end AI solutions for complex Enterprise customers. You will work directly with customers to translate business, data, security, and technical requirements into scalable, production-ready AI architectures.

• Lead technical discovery and translate business requirements into end-to-end AI solution architectures.
• Design solution components, data flows, integrations, model interactions, and operational workflows.
• Define the right AI approach, including RAG, agentic workflows, orchestration, model selection, evaluation, and fine-tuning, balancing quality, security, scalability, latency, and cost.
• Design integrations with customer systems, APIs, data sources, identity services, and IT infrastructure.
• Define evaluation, guardrails, observability, monitoring, governance, and security requirements.
• Lead architecture workshops and technical discussions with customers and internal teams.
• Provide technical leadership to Development and Delivery teams throughout implementation, troubleshooting, and production readiness.
• Build prototypes and POCs, troubleshoot technical issues, and validate architectural decisions through code when needed.

• 5+ years of experience in Software Engineering, Solutions Architecture, AI Engineering, or a related hands-on technical role.
• Proven experience designing and delivering end-to-end Enterprise software or AI solutions.
• Hands-on experience with LLM-based systems, including RAG, agentic workflows, search/knowledge solutions, or similar AI applications.
• Strong understanding of APIs, Enterprise integrations, data flows, databases, and distributed systems.
• Strong understanding of Enterprise environments, including security, identity, networking, and cloud/on-prem/hybrid architectures.
• Experience leading technical discovery and architecture discussions with Enterprise customers.
• Excellent communication skills in English.

Preferred Qualifications

• Experience taking Generative AI solutions from POC to production.
• Experience with LLM evaluation, observability, and guardrails.
• Experience with Kubernetes, microservices, vector databases, search technologies, or data pipelines.
• Experience designing solutions for regulated or security-sensitive environments.