Enterprise Architect

We are seeking a highly experienced Enterprise Architect to design, guide, and govern scalable software solutions across the organization - ranging from individual components to fully integrated enterprise platforms. This role requires strong expertise in AWS cloud technologies, AI infrastructure, and advanced AI governance practices, ensuring solutions align with business strategy, security standards, and responsible AI policies.

Key Responsibilities

• Design end-to-end architectures spanning microservices, APIs, domain platforms, and enterprise ecosystem.
• Define architecture patterns, standards, and reusable framework.
• Translate business requirements into scalable and secure technical solutions.
• Ensure interoperability across systems, data layers, AI services, and platform.
• Develop and maintain enterprise architecture roadmap.
• Align IT strategy with business goals and digital transformation initiatives.
• Establish governance models (TOGAF/SAFe or similar).
• Lead architecture review boards and technical decision-making processes.
• Architect and optimize cloud-native and hybrid solutions using AWS services.
• Define cloud migration strategies and modernization approaches.
• Ensure high availability, resiliency, cost optimization, and performance.
• Implement Infrastructure-as-Code and automation best practices.
• Design AI/ML infrastructure, pipelines, and enterprise integration patterns.
• Architect solutions incorporating LLMs, generative AI, and intelligent agents.
• Establish patterns for RAG, feature stores, and model deployment.
• Guide adoption of AI technologies across enterprise platform.

AI Governance & Observability

• Define and implement enterprise AI governance frameworks (responsible AI, compliance, risk classification).
• Establish observability and monitoring for AI/ML and LLM flows (OpenTelemetry, Langfuse).
• Design guardrails for agent behaviour, HITL workflows, and policy-based control.
• Implement AI lifecycle governance including validation, audit trails, and secure prompt management.

Cross-Disciplinary Leadership

• Act as a strategic liaison across semantic, data, and ML architecture domains.
• Align knowledge graphs, ontologies, data platforms, and ML systems.
• Mentor architects and senior engineers, ensuring cohesive enterprise integration.

Mandatory Skills

• 8-12+ years in software engineering and architecture roles.
• Strong knowledge of microservices, event-driven architectures, API management, and enterprise integration patterns.
• AWS Experience:
• Compute & Containers: EC2, Lambda, ECS/E.
• Networking & Integration: VPC, Route 53, API Gateway, EventBridge, SNS, S.
• Data & Storage: S3, RDS, Aurora, DynamoDB, Redshift.
• Observability: CloudWatch, X‑R.
• Security: IAM, Cognito, KMS, Secrets Manager, Control Tower.
• AI/ML & Observability:
• AWS AI/ML stack: SageMaker, Bedrock, Glue, Lake Formation.
• LLM-based architectures and agent systems.
• AI observability tools (OpenTelemetry, Langfuse, Prometheus/Grafana).
• Strong understanding of AI governance, agent orchestration, and compliance.
• Frameworks & Practices:
• TOGAF or equivalent framework.
• Cloud-native and serverless patterns.
• Integration of semantic, data, and ML architecture.

Nice-to-Have Skills

• AWS Certified Solutions Architect – Professional.
• AWS Specialty Certifications (Machine Learning, Security).
• Experience implementing enterprise AI governance frameworks.
• Background in regulated industry.
• Exposure to multi-cloud or hybrid environments.

Join us in shaping the future of enterprise architecture - where cloud innovation, AI intelligence, and responsible governance converge to drive lasting impact.