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
