- Establish quality standards for AI/LLM features (evaluation, red-teaming, prompt/versioning, regression tests) and drive production readiness.

- Design and run proof-of-concepts (POCs) to validate approaches end-to-end (hypotheses, success metrics, evaluation, cost/latency assessment) and drive learnings into production-ready performant & cost optimized solutions.

- Own and evolve the AI/Search architecture roadmap together with Domain and Group Architecture, balancing customer impact, security, compliance and cost.

- Lead solution design workshops and produce clear technical proposals (including NFRs, risks, migration/rollout plans).

- Define, document and champion best practices (architecture, coding standards, DevSecOps/LLMOps, observability) and lead by example through hands-on delivery and reviews.

- Mentor engineers, provide technical guidance, and help grow a high-performing, inclusive engineering culture.

- Deep proficiency in Java or Kotlin and their ecosystems; proven experience designing and operating large-scale backend systems in production.

- Strong experience with Micronaut or SpringBoot, Terraform, and designing cloud-native microservices (incl.

reliability patterns, performance tuning and cost optimisation).

- Strong knowledge on python using AI & ML focused tools.

- Proven delivery of AI/LLM capabilities end-to-end in production (RAG, orchestration, evaluation, monitoring); hands-on with AWS Bedrock incl. Guardrails and safe rollout patterns.

- Strong applied understanding of ML/AI concepts (embeddings, retrieval, evaluation, privacy/safety considerations) to make pragmatic architecture trade-offs.

- Expertise in data preparation and prompt engineering with a focus on repeatability (versioning), automated evaluation and measurable outcomes.

- Experience with OpenSearch/Elasticsearch, relevance tuning, and operating search at scale.

- Experience with implementing resource-oriented APIs (REST, GraphQL) on client and server side.

- Senior-level cloud architecture expertise on AWS (networking, security, IAM, observability, reliability) and infrastructure as code; able to define standards and reference implementations.

- Demonstrated technical leadership: mentoring, driving alignment across teams, and communicating complex topics to engineering and non-technical stakeholders.

- Experience with data persistence (SQL/noSQL).

- Creating Microservices.

- Good experience with CI/CD, preferably Gitlab CI.

- Ability to design, build, test, and deploy applications.

- Customer centric, passionate about delivering great digital products and services.

- Demonstrating true software craftsmanship mindset.

- Passionate about continuous improvement, collaboration and great teams.

- Strong problem-solving skills coupled with good communication skills.

- Understanding of social and ethical implications of software engineering.

- Open minded, inquisitive, life-long learner.

- Comfortable with ambiguity, highly autonomous.