About us

Appnovation is a global, full-service digital partner that combines Strategy, Experience & Design, Engineering and Managed Services. We build digital solutions that deliver real impact today and serve as foundations for future growth.  Bold ambition. Practical action. Endless possibilities.

ROLE OVERVIEW

In this role, you will design and prototype cutting-edge AI solutions, implement cloud AI architectures, 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, working directly with clients to define solutions and deliver production-ready implementations.

RESPONSIBILITIES 

• AI Solution Architecture: Design and prototype multi-cloud reference architectures leveraging GCP, AWS, and others
• Agentic AI & Integration: Build and implement 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 Engagement: Participate in discovery workshops, present solution architectures, and communicate technical concepts to stakeholders
• Hands-on Development: Prototype solutions, build proof-of-concepts, and implement production AI systems
• Delivery Support: Contribute to project estimation, scoping and technical specifications; uphold delivery KPIs (security, cost, performance)
• Team Collaboration: Work with and mentor engineering teams around AI solutions and orchestrated development practices
• Coordinate: Across internal teams and client stakeholders across timezones

EXPERIENCE 

The ideal candidate will have:

• 7+ years full-stack or platform engineering experience with 2+ years in technical leadership or architecture roles
• ≥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: Ability to facilitate technical discussions and create clear documentation, slides, and architectural diagrams
• Strong technical breadth: Polyglot coding (TypeScript/Node.js, Python, Java), AI ecosystem knowledge (LangChain, LangGraph), MLOps practices
• Prototyping mindset: Experience building proof-of-concepts and production-ready AI implementations

TECHNOLOGIES 

• An understanding of the following, or comparative, technologies:
  • AI Platforms: LangChain, AutoGen, CrewAI, LangGraph, Pydantic AI, PyTorch, TensorFlow, Unsloth, Vertex AI, AWS Bedrock, Azure OpenAI, multi-modal AI 
  • Data & Vector Systems: Milvus, Pinecone, Qdrant, RAG pipelines, embeddings 
  • Development: AI coding assistants (Cursor, Cline, Windsurf, Claude Code), Next.js, Nuxt.js, React Native
  • CMS & Infrastructure: Contentful, Sanity, Builder.io, Adobe AEM, Terraform, microservices

PREFERRED QUALIFICATIONS

• Cloud certifications (GCP ML Engineer, AWS ML Specialty)
• Google Professional Cloud Architect or Google Professional Cloud Developer
• Enterprise AI governance and regulatory compliance knowledge