Senior Generative AI / AI Solution Architect

Who We Are

We operate beyond organizational silos, combining deep expertise in data engineering and AI-driven solutions to design and deliver scalable, user-centric applications and modern data architectures. We support a wide range of industries, including Automotive, Banking, Insurance, Telecommunications, E-commerce, and Public Services.

Our focus is on building robust, enterprise-grade data and AI platforms and enabling advanced analytics and AI capabilities across leading cloud ecosystems, including AWS and Microsoft Azure, as well as Microsoft Fabric and the Power Platform. We specialize in designing secure, scalable, high-performance solutions that integrate data platforms, AI models, and Generative AI use cases to deliver real business value.

What you'll be doing

• Design end-to-end architectures for Generative AI, agentic AI, enterprise knowledge solutions, document automation, and intelligent workflows.
• Define agent architectures covering orchestration, tools, APIs, state and memory management, retrieval, model routing, human-in-the-loop patterns, observability, and failure recovery.
• Design enterprise RAG solutions using semantic and hybrid search, vector and graph-based retrieval, metadata filtering, access controls, citations, reranking, evaluation, and feedback loops.
• Architect foundation-model integration and model gateway patterns, including model selection, routing, fallback strategies, prompt and context management, safety controls, latency, and cost-performance optimization.
• Develop document intelligence and structured-generation patterns for proposals, reports, validation workflows, and engineering artefacts.
• Design scalable serverless, containerized, API-based, and event-driven solutions across AWS, hybrid, and on-premises environments.
• Define security, identity, networking, observability, evaluation, deployment, governance, and LLMOps standards for production AI solutions.
• Build prototypes and reference implementations to validate architectural approaches and emerging technologies.
• Review solution designs and code, resolve critical technical challenges, and provide technical guidance to engineering teams.
• Mentor engineers and contribute to architecture standards, best practices, and technology decisions across projects.

What you'll bring along

• At least 8 years of relevant experience across software engineering, cloud, data, platform engineering, or AI, including significant experience designing enterprise-scale solutions.
• Proven experience designing and delivering production AI and machine-learning solutions.
• Strong hands-on experience designing and delivering production Generative AI and LLM solutions, including RAG, embeddings, retrieval, evaluation, guardrails, and agentic workflows.
• Strong software engineering background, preferably with hands-on Python experience and familiarity with one or more additional languages such as Java, C#, TypeScript/JavaScript, Go, or equivalent.
• Strong understanding of REST, gRPC, asynchronous processing, event-driven architectures, and enterprise integration patterns.
• Proven architecture experience across public cloud and hybrid, private-cloud, or on-premises environments.
• Hands-on experience with AWS AI and application services, including Amazon Bedrock or comparable foundation-model platforms.
• Experience designing retrieval architectures using technologies such as Amazon OpenSearch, PostgreSQL/pgvector, vector databases, and/or graph-based retrieval systems.
• Strong knowledge of IAM, private networking, secrets management, observability, CI/CD, infrastructure as code, AI evaluation, safety, and production LLMOps.
• Strong understanding of production AI considerations such as scalability, reliability, latency, security, governance, and cost optimization.
• Strong client-facing consulting and technical communication skills, with the ability to translate complex business requirements into scalable technical solutions.
• A high degree of ownership, collaboration, technical decision-making, and mentoring capability.
• Excellent command of both spoken and written English.

Nice to have

• Experience with Amazon Bedrock AgentCore, Bedrock Guardrails, AWS Glue, Lambda, ECS, or EKS.
• Experience with LiteLLM, open-source models, model gateways, or multi-model architectures.
• Experience with knowledge graphs and graph-based retrieval.
• Experience with Azure AI or other enterprise AI platforms.
• Experience designing AI solutions for regulated or security-sensitive environments.
• Relevant AWS, Azure, AI, cloud, or architecture certifications.