Enterprise Architect

Virtusa•Piscataway, NJ

15d

About The Position

Enterprise Architect Key Responsibilities Architecture Leadership: Define and maintain the enterprise architecture blueprint across business, data, application, and technology domains. Lead modernization initiatives leveraging microservices-based architecture and API-first design. API & Microservices Engineering: Design, govern, and evolve enterprise API ecosystems (REST, GraphQL, gRPC). Implement and standardize API gateway patterns, security, rate limiting, and observability (e.g., Kong, Apigee, Boomi, AWS API Gateway). Guide teams in building and orchestrating microservices using containers, Kubernetes, and event-driven architectures. Agentic AI Integration: Architect and operationalize Agentic AI frameworks that use LLMs, embeddings, and autonomous agents for enterprise use cases (e.g., knowledge orchestration, intelligent workflows, customer interaction). Integrate AI pipelines with existing systems using tools such as LangChain, OpenAI, Anthropic, or vector databases. Ensure AI systems align with enterprise governance, security, and compliance frameworks (Responsible AI, model transparency, data lineage). Technology Governance & Standards: Establish architecture principles, reference models, and technology standards. Conduct architecture reviews to ensure solution alignment with enterprise strategy. Partner with InfoSec and Data teams to enforce Zero Trust, API security, and ethical AI use. Collaboration & Influence: Work closely with product, data, and AI engineering teams to translate business goals into scalable architecture solutions. Serve as a trusted advisor to executives, ensuring technology investments deliver measurable business outcomes. Required Skills & Experience Education: Bachelor’s or Master’s degree in Computer Science, Engineering, or related field. Experience: 10+ years in enterprise architecture, with hands-on design and implementation experience. Technical Expertise: Proven experience with API platforms (Kong, Apigee, Boomi, AWS API Gateway). Strong in microservices design patterns, container orchestration (Docker/Kubernetes), and event streaming (Kafka, RabbitMQ). Deep understanding of LLMs, embeddings, RAG pipelines, and agentic AI orchestration frameworks (LangChain, OpenDevin, CrewAI, etc.). Familiarity with cloud-native platforms (AWS, Azure, GCP) and DevOps toolchains (Terraform, GitHub Actions, ArgoCD). Architecture Frameworks: TOGAF, Zachman, or similar enterprise frameworks. • Soft Skills: Strong communication, stakeholder management, and ability to bridge business and technology

Requirements

Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
10+ years in enterprise architecture, with hands-on design and implementation experience.
Proven experience with API platforms (Kong, Apigee, Boomi, AWS API Gateway).
Strong in microservices design patterns, container orchestration (Docker/Kubernetes), and event streaming (Kafka, RabbitMQ).
Deep understanding of LLMs, embeddings, RAG pipelines, and agentic AI orchestration frameworks (LangChain, OpenDevin, CrewAI, etc.).
Familiarity with cloud-native platforms (AWS, Azure, GCP) and DevOps toolchains (Terraform, GitHub Actions, ArgoCD).
TOGAF, Zachman, or similar enterprise frameworks.
Strong communication, stakeholder management, and ability to bridge business and technology

Responsibilities

Define and maintain the enterprise architecture blueprint across business, data, application, and technology domains.
Lead modernization initiatives leveraging microservices-based architecture and API-first design.
Design, govern, and evolve enterprise API ecosystems (REST, GraphQL, gRPC).
Implement and standardize API gateway patterns, security, rate limiting, and observability (e.g., Kong, Apigee, Boomi, AWS API Gateway).
Guide teams in building and orchestrating microservices using containers, Kubernetes, and event-driven architectures.
Architect and operationalize Agentic AI frameworks that use LLMs, embeddings, and autonomous agents for enterprise use cases (e.g., knowledge orchestration, intelligent workflows, customer interaction).
Integrate AI pipelines with existing systems using tools such as LangChain, OpenAI, Anthropic, or vector databases.
Ensure AI systems align with enterprise governance, security, and compliance frameworks (Responsible AI, model transparency, data lineage).
Establish architecture principles, reference models, and technology standards.
Conduct architecture reviews to ensure solution alignment with enterprise strategy.
Partner with InfoSec and Data teams to enforce Zero Trust, API security, and ethical AI use.
Work closely with product, data, and AI engineering teams to translate business goals into scalable architecture solutions.
Serve as a trusted advisor to executives, ensuring technology investments deliver measurable business outcomes.