Solution Architect

Architect and govern enterprise-scale Java solutions, ensuring secure, resilient, and high-performance platforms. Translate strategic business objectives into robust technical designs leveraging Java/Spring Boot, microservices, and cloud-native patterns. Define and drive integration strategies (APIs, messaging, caching), cloud adoption (AWS/Azure/GCP), and database architectures (SQL/NoSQL) with production-grade reliability. Champion AI-enabled development by embedding LLM/RAG capabilities, model serving, MLOps, and prompt engineering into solutions, while enforcing best practices for security, observability, scalability, and cost optimization.

Accountability 1

• Design and enforce microservices-based architectures with best practices for modularity, observability, resiliency, and maintainability.
• Establish

  coding standards, design patterns, and quality gates

  for Java services (Clean Architecture, DDD, Hexagonal architecture).
• Define and govern

  API-first

  integration strategies (REST, GraphQL where relevant) and

  event-driven

  messaging (Kafka/RabbitMQ).
• Ensure

  enterprise-grade interoperability

  across internal systems and SaaS applications; drive schema evolution/versioning best practices.
• Evaluate and recommend services on

  AWS (must)

  , Azure/GCP are a plus. Enable cloud-native patterns (autoscaling, serverless components, managed DBs).
• Optimize for performance, security, reliability and

  total cost of ownership (TCO)

  . implement multi-region HA/DR where required.
• Set and enforce guardrails for

  SSO

  (OAuth2/OIDC/SAML), secrets management, least-privilege access, and secure integration across internal/SaaS ecosystems.
• Embed

  data protection

  (encryption at rest/in transit), threat modeling, and

  AI-specific privacy controls

  (prompt/response sanitization, content filters).
• Drive

  CI/CD

  and automation for Java services and AI components; promote trunk-based development, blue/green/canary deployments.
• Implement

  observability

  (logs, metrics, traces) via

  ELK/Graylog, Prometheus/Grafana, Jaeger/Zipkin

  ; integrate APM (New Relic/AppDynamics).
• Review and validate solution designs, conduct architecture assessments pre-/post-go-live.
• Maintain

  architectural documentation

  , decision logs, reusable patterns, and reference blueprints (including AI/RAG patterns).
• Provide technical leadership, coach teams on architecture principles, coding standards, and design patterns. manage stakeholders effectively.
• Integrate AI services and SDKs with Java microservices (e.g.,

  Azure OpenAI/OpenAI

  ,

  AWS Bedrock

  ,

  Vertex AI

  ,

  Azure ML/SageMaker

  endpoints) via

  REST/gRPC

  .
• Define

  prompt engineering

  practices,

  evaluation frameworks

  (automatic + human-in-the-loop), guardrails, and

  Responsible AI

  guidelines (bias, privacy, toxicity filters, PII protection).

Accountability 2

• Design trade-offs: scalability vs. cost, latency vs. consistency, build vs. buy (SaaS).
• Operational excellence: CI/CD, observability, incident response, performance tuning.
• Security & compliance: identity, data protection, threat modeling, posture in multi-tenant SaaS.
• Stakeholder influence: cross-functional collaboration, governance, documentation, coaching.
• Track key metrics: CPU/memory utilization, DB query latency, cache hit ratio, replication lag, and API response times.
• Use Prometheus and Grafana for real-time metrics visualization and alerting.
• Implement centralized logging using ELK stack or Graylog for microservices and database events.
• Use distributed tracing tools like Jaeger or Zipkin to monitor service-to-service communication.
• Enable database health checks and query performance dashboards using Grafana and Prometheus.
• Implement distributed caching strategies using Redis or Memcached to reduce latency and improve application performance.
• Leverage CDN-based caching for static content and edge optimization.
• Design solutions leveraging cloud-native databases such as Amazon Aurora, DynamoDB.
• Implement multi-region replication and automated failover for high availability and disaster recovery.