Generative AI Solution Architect

• Design and deliver scalable, resilient, and secure enterprise-grade solutions, ensuring alignment with business goals and technical strategy
• Lead architecture design sessions and guide engineering teams through hands-on prototyping, implementation, and best practices
• Collaborate closely with clients to understand needs, define outcomes, and translate business challenges into actionable architectural blueprints
• Drive modernization initiatives leveraging cloud-native technologies, data platforms, and event-driven systems
• Integrate Generative AI components into solutions, applying frameworks, APIs, and vector databases to achieve measurable impact
• Communicate complex technical concepts clearly to executive stakeholders, contributing to discovery workshops, demos, and pre-sales activities

• 8+ years of experience in software development and solution architecture, with a proven record of delivering enterprise solutions
• Strong coding proficiency and ability to prototype, automate, and collaborate with engineering teams across multiple technologies
• Hands-on expertise with at least one major cloud platform (Azure, AWS, or GCP) and familiarity with containers, Kubernetes, and Infrastructure as Code
• Solid understanding of data engineering, integration patterns, data governance, and privacy-by-design principles
• Practical experience or strong theoretical grounding in Generative AI, including orchestration frameworks (LangChain, LlamaIndex), vector databases, and model APIs
• Excellent client engagement, communication, and presentation skills, with the ability to manage ambiguity and deliver results in complex environments
• Fluency in English, both written and spoken
• Openness to occasional travel for key client engagements, such as workshops, project kick-offs, or strategic planning sessions

Nice to have

• Experience with Multimodal AI, including vision/OCR, audio (TTS/STT), video processing, document intelligence, or synthetic data generation
• Background in domain-specific environments such as Financial Services, Retail, Life Sciences & Healthcare, or other regulated industries
• Understanding of AI security and risk management, including prompt injection, data poisoning, and third-party model vulnerabilities
• Familiarity with UX design for AI assistants, human-in-the-loop review systems, and enterprise-scale adoption or change management