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.
Responsibilities:
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.
Requirements:
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.
