Responsibilities
- Lead technical pre-sales activities, including discovery sessions, client workshops, and RFP/RFI responses.
- Manage stakeholders, advise customers, gather requirements, articulate solution trade-offs, and communicate effectively across business and technical audiences.
- Kick off customer projects for custom development services, ensuring a smooth transition into delivery.
- Design architectures for enterprise systems and digital products across iGaming, Aviation, and Healthcare.
- Contribute to company-wide AI adoption, including the rollout of AI tools and definition of optimisation guidelines.
- Conduct technical interviews for Solution Architect and Tech Lead roles on request.
Requirements
- 5+ years of software development experience with at least one of: Python, Java, Node.js
- 3+ years in a solution architecture function within a service or product company
- Experience leading and mentoring one or more software development teams
- Working experience with Lean / Agile / Scrum and team scaling frameworks (SAFe, LeSS, or equivalent)
- Demonstrable experience in pre-sales activities (RFP/RFI, discovery workshops, technical proposals)
- English proficiency at minimum B2 level (CEFR), spoken and written
- Databases (RDBMS and NoSQL)
- Architectural styles and design patterns
- Security patterns, computer security, and networking vulnerabilities
- High-load systems design
- Cloud providers: AWS, Azure, or GCP
- Microservices architecture (modular, scalable system design)
- Event-driven architecture (Kafka, RabbitMQ, or cloud-native messaging services)
- CI/CD principles and tools (Bitbucket Pipelines, GitLab CI, Argo, etc.) and deployment strategies
- Containerisation and orchestration; Kubernetes; hybrid cloud
- Security posture, data privacy, and data protection in software development
- Cloud AI services: working knowledge of AWS (SageMaker, Bedrock), Azure (Cognitive / AI Services), or GCP (Vertex AI)
- Generative AI and LLM landscape, including SaaS vs. self-managed trade-offs and model selection criteria
- Security in AI solutions: secure model handling, data anonymisation, compliance considerations
Nice to Have
- Industry experience in iGaming, Aviation, or Healthcare, including familiarity with relevant regulatory contexts (e.g., gambling licensing, aviation safety standards, HIPAA/GDPR)
- Agentic AI architecture: design patterns, frameworks, and orchestration tools (LangGraph, MCP, A2A)
- Cloud provider Architect or Engineer certifications
- AI Platform Architect badges or equivalent vendor credentials
