AI Solution Architect

Job Title

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

Generative AI & Agent Technologies (2+ Years)

Hands-on experience architecting and building GenAI Agent solutions using LangChain, LangGraph, CrewAI, AutoGen, 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

Solution & Enterprise Architecture

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)

Technology Stack (Hands-On Proficiency)

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, MuleSoft, or Istio

Familiarity with frontend frameworks (React, Angular) and mobile patterns sufficient to define end-to-end solution architectures

DevOps & Platform Engineering (Exposure & Understanding)

Good understanding of CI/CD pipeline design using Jenkins, GitHub Actions, GitLab CI, or Azure DevOps — 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 CloudFormation, or AWS CDK for cloud provisioning governance

Familiarity with observability stacks: AWS CloudWatch, Prometheus, Grafana, ELK Stack — able to define non-functional requirements and monitoring strategies

Appreciation of DevSecOps practices: SAST/DAST tooling, secrets management (HashiCorp Vault, AWS Secrets Manager), and shift-left security in the SDLC

Transformation Program & Stakeholder Management Solution Architecture & SDLC Transformation Domain Experience

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)