Generative AI & Agent Technologies

About the Role

We are seeking a seasoned architect with 15+ years of enterprise software engineering and architecture experience, holding a bachelor’s or master’s degree in Computer Science, Software Engineering, or a related technical discipline. The ideal candidate will have a proven track record as a Solution Architect or Enterprise Architect across large-scale, complex programs spanning multiple business domains and technology stacks, with a focus on digital and AI-driven transformation.

Responsibilities

• Architect and build Generative AI Agent solutions using frameworks such as LangChain, LangGraph, CrewAI, AutoGen, or MCP Protocol.
• Design enterprise-grade Retrieval-Augmented Generation (RAG) pipelines, vector stores, and knowledge graph integrations.
• Apply prompt engineering techniques, including Chain-of-Thought, few-shot/zero-shot strategies, and responsible-AI guardrails.
• Define target-state architectures, architecture roadmaps, and transition architectures aligned to business strategy.
• Govern architecture across programs through Architecture Review Boards (ARB), design authority participation, and architecture decision records (ADR).
• Design and review polyglot architectures spanning Java and .NET ecosystems, selecting the right stack for each capability.
• Lead digital and AI-driven transformation programs, including stakeholder management.
• Define non-functional requirements and monitoring strategies for observability stacks (e.g., AWS CloudWatch, Prometheus, Grafana, ELK Stack).
• Apply integration patterns such as event-driven architecture (EDA), API-led connectivity, microservices, CQRS, and Saga patterns.

Requirements

• 15+ years of enterprise software engineering and architecture experience.
• Bachelor’s or master’s degree in Computer Science, Software Engineering, or a related technical discipline.
• 2+ years of hands-on experience with Generative AI & Agent Technologies.
• Strong knowledge of LLM APIs: Anthropic Claude, OpenAI GPT-4o, Azure OpenAI (including model selection, context management, and cost optimization).
• Experience with cloud AI platforms: AWS Bedrock.
• Deep expertise in solution architecture disciplines: capability modeling, application architecture, integration architecture, data architecture, and security architecture.
• Proficiency with architecture frameworks: TOGAF, Zachman, or equivalent.
• Experience with cloud architecture principles across AWS, Azure, or GCP, including multi-cloud and hybrid strategies.

Skills

• 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, Cosmos DB.
• API gateway and service mesh technologies: Kong, Apigee, AWS API Gateway, MuleSoft, Istio.
• Frontend frameworks: React, Angular (sufficient to define end-to-end solution architectures).
• CI/CD pipeline design: Jenkins, GitHub Actions, GitLab CI, Azure DevOps.
• Containerization and orchestration: Docker, Kubernetes (EKS, AKS, GKE), Helm, Istio.
• Infrastructure-as-Code: Terraform, AWS CloudFormation, AWS CDK.
• DevSecOps practices: SAST/DAST tooling, secrets management (HashiCorp Vault, AWS Secrets Manager), shift-left security in the SDLC.

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).