Technical AI Architect – GenAI & Agentic AI Operations

Company Description

Space Inventive

is an innovative and dynamic company that specializes in leading businesses through transformative journeys in the digital era. They are pioneers in driving innovation and helping organizations transition into digitally mature entities. With a wide range of cutting-edge services, including web enterprise application development, AI & ML development, cloud engineering, data engineering, and business intelligence, Space craft’s tailor-made solutions to meet each client’s unique challenges. Their integrated approach combines strategic vision with digital expertise, empowering businesses to create new models, modernize legacy systems, and launch market-ready digital products and platforms.

Role Description

We are seeking a Technical AI Architect to lead the architecture, governance, and operational readiness of our AI application Operations portfolio, including Generative AI, Agentic AI, and custom AI applications . The role should also cover the review and approval of technical artifacts, such as the Architecture handbook, IQ/OQ’s, and ITOH, as well as the creation and update of any technical documents from a technical point of view. The Technical Architect should align with the L3 technical support team and business for Implementations and smooth Operations, and act as the transition lead during the handover from delivery to Operations during the application transition.

Key Responsibilities

• Lead end-to-end architecture for GenAI, Agentic AI, ML-enabled, and custom AI applications .
• Define secure, scalable, resilient, and reusable architecture patterns for AI solutions.
• Guide technical enhancements, upgrades, integrations, migrations, and implementation activities.
• Review and approve key technical artifacts, including Architecture Handbook, IQ/OQ, ITOH, technical design documents, runbooks, and transition documents .
• Create and maintain technical documentation from an architecture and operations perspective.
• Act as the technical transition lead during handover from delivery to operations.
• Ensure applications meet production readiness, monitoring, supportability, security, and compliance requirements.
• Partner with L3 support teams to resolve complex technical issues, support root cause analysis, and improve application stability.
• Align with business and technical stakeholders to ensure smooth implementations and ongoing operations.
• Promote responsible AI practices, including governance, privacy, traceability, risk controls, and auditability.

Required Skills and Experience

• Strong experience as a Technical Architect, AI Architect, Solution Architect, or Enterprise Application Architect .
• Hands-on knowledge of Generative AI, LLMs, Agentic AI, RAG, prompt engineering, vector databases, AI orchestration frameworks, and model integration .
• Experience with AI platforms such as Azure OpenAI, OpenAI, AWS Bedrock, Google Vertex AI , or similar.
• Strong understanding of cloud architecture , preferably Azure, including APIs, microservices, DevOps, CI/CD, containers, security, monitoring, and integration patterns.
• Experience designing and supporting enterprise-grade AI or data-driven applications in production.
• Knowledge of IT operations, L2/L3 support models, incident/problem/change management, release management, SLAs, and operational handover .
• Strong documentation and technical review skills for architecture, validation, transition, and operational documents.
• Understanding of security, privacy, compliance, responsible AI, and risk management practices.
• Experience in regulated environments and familiarity with IQ/OQ, ITOH, GxP, CSV, or validation documentation is preferred.

Qualifications

• Bachelor’s or master’s degree in computer science, Engineering, IT, Data Science, AI, or related field.
• 10+ years of IT experience, with 5+ years in architecture or technical leadership.
• 3+ years of experience with AI, ML, GenAI, intelligent automation, or advanced analytics applications.
• Experience working with business, delivery, operations, security, infrastructure, and L3 support teams.
• Preferred certifications: Azure/AWS/GCP Architect, AI/ML, ITIL, TOGAF , or equivalent practical experience.