AI Solutions & Development Director, Appnovation

• 10+ years full-stack or platform engineering experience with 3+ years directing delivery teams
• ≥2 years hands-on GenAI: building production LLM applications, prompt engineering, integrating AI coding assistants and autonomous agent frameworks
• Multi-cloud expertise: GCP (Vertex AI) or AWS (Bedrock, Guardrails)
• Security-first approach: GenAI-specific threat modeling and guardrails implementation
• Client communication: Workshop facilitation and storytelling through documents, slides, architectural diagrams
• Technical breadth: Polyglot coding (TypeScript/Node.js, Python, Java), AI ecosystem knowledge (LangChain, LangGraph), MLOps practices
• Advanced AI experience: Fine-tuning/RLHF, modern frameworks (Vercel AI SDK, Mastra.ai)
• An understanding of the following, or comparative, technologies:
• AI Platforms: LangChain, AutoGen, CrewAI, LangGraph, PyTorch, TensorFlow, Vertex AI, AWS Bedrock, Azure OpenAI, multi-modal AI
• Data & Vector Systems: Milvus, Pinecone, Qdrant, RAG pipelines, embeddings
• Development: AI coding assistants (Cline, Roocode, Claude Code), Next.js, Nuxt.js, React Native, Flutter
• CMS & Infrastructure: Contentful, Sanity, Builder.io, Adobe AEM, Terraform, microservices
• Security: OWASP GenAI guidelines, enterprise AI security frameworks

Desirable

• As the Technical Director - AI Solutions & Development, you will lead the architecture and delivery of cutting-edge AI solutions, oversee multi-cloud AI implementations, and help guide our continued evolution in AI-driven development practices
• This hands-on role combines deep technical expertise with the ability to translate complex AI concepts into business value for our diverse client base
• AI Solution Architecture: Design multi-cloud reference architectures leveraging GCP, AWS, and potentially China-mainland clouds when solution sovereignty demands it
• Agentic AI & Integration: Apply agentic-LLM patterns, RAG pipelines, and architect solutions with embeddings, vector databases, MCP servers, and AI coding tools
• Security & Compliance: Embed OWASP GenAI risk mitigations and security best practices across SDLC with AI observability and strong monitoring
• Client Leadership: Lead discovery workshops, craft solution architecture, and run executive readouts for stakeholders
• Delivery: Estimate, scope and price projects; uphold delivery KPIs (security, cost, performance)
• Team Development: Build and mentor engineering teams around AI solutions and orchestrated development practices
• Coordinate across internal teams and client stakeholders across timezones