Solution Architect

Technical Skills

• Event-driven architecture at scale (Kafka, Pub/Sub, SNS/SQS)
  • Able to discuss topology, publisher/consumer patterns, failure handling, and scalability.
• API-led design
  • REST and/or gRPC.
  • High-throughput HTTP ingestion.
  • Schema design, authentication, and versioning.
• Distributed data stores
  • Operational, non-relational databases.
  • No focus on data warehousing or OLAP.
• Cloud platforms
  • Strong AWS experience (essential).
  • GCP experience desirable.
  • Azure-only profiles not suitable.
• ML data pipelines
  • Designing pipelines that feed machine learning models.
  • Focus on model input rather than reporting or dashboards.
• ML platform knowledge
  • Feature stores.
  • Model serving.
  • Infrastructure supporting ML model consumption.
• Streaming data enrichment
  • Real Time stream processing, aggregation, and enrichment.
• Hands-on technical expertise
  • Recent implementation experience, not purely architectural governance.

Architecture

• Ownership of non-functional requirements:
  • Performance
  • Scalability
  • Resilience
  • Fault tolerance
  • Operability
• Produces clear architecture documentation:
  • High-Level Designs (HLDs)
  • Low-Level Designs (LLDs)
  • System and data flows
  • Edge-case and operational considerations
• Comfortable presenting to Architecture Review Boards.
• Strong trade-off analysis:
  • Identifies risks early.
  • Explains technical and business impacts of design decisions.

Collaboration & Communication

• Works closely with:
  • Product teams
  • Engineering teams
  • Data Science teams
• Able to explain complex architectures clearly to both technical and non-technical audiences.
• Collaborative mindset:
  • Takes ownership.
  • Welcomes feedback.
  • Iterates quickly with adjacent teams.

Nice-to-Have Skills

• Vector databases
  • Semantic search.
  • Embedding-based similarity search.
• Knowledge graph databases
  • Neo4j or equivalent.
  • Graph traversal and relationship modelling.
• LLM integration
  • RAG.
  • Embedding pipelines.
  • Agent orchestration.
• Recommendation systems
  • Infrastructure supporting personalization and recommendation engines.
• Observability
  • Distributed tracing.
  • Structured logging.
  • Alerting.
  • Understanding of operational failures at scale.
• Cost-aware cloud architecture
  • Designs with cloud spend optimisation in mind across compute, storage, and high-volume workloads.

Do Not Submit IFG

You are a candidate whose background is primarily focused on:

• Data modelling.
• Data warehousing.
• Business Intelligence (BI)/Reporting.
• ETL/ELT engineering.
• Regulatory, compliance, or FinOps architecture.
• SAP technical architecture.
• Azure-only cloud environments.
• Enterprise or governance architects with no recent hands-on technical delivery.

Technical Currency (Very Important)

Architects with 5-10+ years of experience must still demonstrate recent hands-on work.

Look for:

• Implementation language
  • Built, implemented, configured (not only designed or defined).
• Technology specificity
  • Concrete tools, patterns, architectures, and configurations.
• Recent experience
  • Hands-on implementation within the last 2-3 years.
• Continuous learning
  • Recent certifications, new technologies, or modern tooling are a strong positive indicator.