AI Solution Architect

Job Description

• 15+ years of enterprise software engineering and architecture experience with a bachelor's or master's degree in computer science, Software Engineering, or a related technical discipline
• Proven track record as a Solution Architect or Enterprise Architect across large-scale, complex programs spanning multiple business domains and technology stacks
• Extensive experience leading digital and AI-driven transformation programs, including stakeholder management.

• Hands‑on experience architecting and building GenAI Agent solutions using Lang Chain, Lang Graph, CrewAI, Auto Gen, or MCP Protocol
• Strong knowledge of LLM APIs:
  Anthropic Claude, OpenAI GPT‑4o, Azure OpenAI — including model selection, context management, and cost optimization
• Experience designing enterprise‑grade Retrieval‑Augmented Generation (RAG) pipelines, vector stores and knowledge graph integrations
• Proficiency in prompt engineering techniques:
  Chain‑of‑Thought, few‑shot/zero‑shot strategies, and responsible‑AI guardrails
• Exposure to cloud AI platforms: AWS Bedrock

• Deep expertise in solution architecture disciplines: capability modelling, application architecture, integration architecture, data architecture, and security architecture
• Hands‑on experience defining target‑state architectures, architecture roadmaps, and transition architectures aligned to business strategy
• Proficiency with architecture frameworks and methodologies: TOGAF, Zachman, or equivalent enterprise architecture frameworks
• Extensive experience with integration patterns: event‑driven architecture (EDA), API‑led connectivity, microservices, CQRS, and Saga patterns
• Strong understanding of cloud architecture principles across AWS, Azure, or GCP — including multi‑cloud and hybrid strategies
• Experience governing architecture across programs:
  Architecture Review Boards (ARB), design authority participation, and architecture decision records (ADR)

• Java / J2EE:
  Java 11–21, Spring Boot, Spring Framework, Jakarta EE, microservices with REST/gRPC, Apache Kafka, JPA/Hibernate, PostgreSQL, Oracle
• .NET: C# (.NET 6/7/8), ASP.NET Core Web API, Entity Framework Core, Azure Service Bus, Dapper, SQL Server, and Cosmos DB
• Strong ability to design and review polyglot architectures spanning both Java and .NET ecosystems, selecting the right stack for each capability
• Hands‑on experience with API gateway and service mesh technologies:
  Kong, Apigee, AWS API Gateway, Mule Soft, or Istio
• Familiarity with frontend frameworks (React, Angular) and mobile patterns sufficient to define end‑to‑end solution architectures

• Good understanding of CI/CD pipeline design using Jenkins, Git Hub Actions, Git Lab CI, or Azure Dev Ops — able to define standards and review pipeline architectures
• Working knowledge of containerization and orchestration:
  Docker, Kubernetes (EKS, AKS, GKE), Helm, and Istio service mesh
• Understanding of Infrastructure‑as‑Code:
  Terraform, AWS Cloud Formation, or AWS CDK for cloud provisioning governance
• Familiarity with observability stacks: AWS Cloud Watch, Prometheus, Grafana, ELK Stack — able to define non‑functional requirements and monitoring strategies
• Appreciation of Dev Sec Ops  practices: SAST/DAST tooling, secrets management (Hashi Corp Vault, AWS Secrets Manager), and shift‑left security in the SDLC

• Experience in the life insurance domain: underwriting, claims processing, policy administration, or actuarial tooling
• Knowledge of insurance regulatory and data‑governance standards (SOX, GDPR equivalents)

• Experience in the life insurance domain: underwriting, claims processing, policy administration, or actuarial tooling
• Knowledge of insurance regulatory and data‑governance standards (SOX, GDPR equivalents)

• Experience in the life insurance domain: underwriting, claims processing, policy administration, or actuarial tooling
• Knowledge of insurance regulatory and data‑governance standards (SOX, GDPR equivalents)