Chennai, Tamil Nadu
Job Summary
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
Key Responsibilities
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
Skill Requirements
Transformation Program & Stakeholder Management
Extensive experience leading or playing a senior architecture role within large-scale digital, AI, or cloud transformation programs
Proven ability to engage and influence senior stakeholders: C-suite executives, program directors, business sponsors, and third-party vendors
Strong experience translating complex technical architectures into clear business narratives, investment cases, and executive presentations
Ability to manage architecture across multiple concurrent workstreams, resolving cross-program dependencies and architectural conflicts
Familiarity with delivery frameworks: SAFe, Agile— able to adapt architecture governance to the delivery model in use
Solution Architecture & SDLC Transformation
Demonstrated experience leading architecture reviews, technical road-mapping, and design-pattern governance across enterprise programs
Ability to transform traditional SDLC processes with AI-assisted development, automated testing, and DevSecOps practices at program scale
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)
Soft Skills & Professional Competencies
Excellent written communication skills — ability to produce clear architecture documents, solution proposals, and executive summaries tailored to both technical and non-technical audiences
Strong verbal communication — able to articulate complex AI and enterprise architecture concepts confidently in design workshops, steering committees, and board-level presentations
Stakeholder engagement — proven ability to build trusted relationships with business leaders, product owners, delivery teams, and third-party partners to drive architectural alignment
Collaborative team player — comfortable leading architecture guilds and working across distributed delivery teams while also being self-driven in individual design and analysis
Mentoring & knowledge sharing — willingness to coach engineers and solution designers, promote architecture best practices, and build technical capability across the organization
Analytical thinking — structured problem-solver who can navigate ambiguity, assess architectural trade-offs, and propose pragmatic, scalable solutions under program pressure
Adaptability — thrives in fast-moving transformation environments where AI technologies, business priorities, and regulatory requirements evolve rapidly
Other Requirements
1. Microsoft Certified: Azure Solutions Architect Expert (Recommended)
#body.unify div.unify-button-container .unify-apply-now: focus, #body.unify div.unify-button-container .unify-apply-#body.unify div.unify-button-container .unify-apply-now: focus, #body.unify div.unify-button-container .unify-apply-
