Solution Architect

Job Summary

We are seeking a highly experienced Solution Architect to design, guide, and govern scalable software solutions across the Capital Markets analytics platforms. This role requires strong expertise in traditional client-server architecture, AWS cloud technologies, AI infrastructure, and advanced AI governance practices, ensuring solutions align with business strategy, security standards, and responsible AI policies.

Responsibilities

• Architecture Solution Design
• Design end-to-end solution architectures spanning:
• Component-level services (microservices, APIs)
• Domain platforms
• Define architecture patterns, standards, and reusable frameworks
• Translate business requirements into scalable and secure technical solutions
• Ensure interoperability across systems, data layers, AI services, and platforms
• Cloud Architecture (AWS)
• 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
• AI, Data Intelligent Systems Architecture
• Design AI/ML infrastructure, pipelines, and enterprise integration patterns
• Architect solutions incorporating LLMs, generative AI, and intelligent agents
• Guide adoption of AI technologies within enterprise platforms and products
• Establish patterns for:
• RAG (Retrieval-Augmented Generation)
• Feature stores and data pipelines
• Model deployment, versioning, and scaling
• AI Governance, Observability Control
• Define and implement enterprise AI governance frameworks covering:
• Responsible AI usage (fairness, bias mitigation, explainability)
• Data privacy, lineage, and compliance
• AI risk classification and policy enforcement
• Establish AI observability and monitoring capabilities, including:
• End-to-end tracing of AI/ML and LLM flows using tools such as OpenTelemetry
• Monitoring of prompts, responses, latency, and model behavior using platforms like Langfuse or equivalent
• Metrics for model performance, drift, hallucination rates, and usage patterns
• Design and enforce agent governance and control mechanisms, including:
• Monitoring and auditing of autonomous and semi-autonomous AI agents
• Guardrails for agent behavior, tool usage, and decision boundaries
• Human-in-the-loop (HITL) workflows and escalation patterns
• Policy-based control over agent actions and integrations
• Implement AI lifecycle governance, including:
• Model validation, approval workflows, and audit trails
• Continuous evaluation and feedback loops
• Secure model and prompt management
• Cross-Disciplinary Architecture Leadership
• Act as a strategic liaison across Semantic, Data, and ML architecture domains
• Facilitate alignment between knowledge graphs, ontologies, data platforms, and ML systems
• Provide architectural guidance to specialized architects, ensuring cohesive enterprise integration
• Bridge gaps between business semantics, data engineering, and machine learning pipelines
• Security, Compliance Governance
• Ensure architectures meet enterprise security standards (e.g., Zero Trust)
• Define policies for data governance, access control, and auditability
• Align AI and cloud solutions with regulatory and compliance frameworks
• Collaboration Leadership
• Work with engineering, product, data, and AI teams to align solutions
• Mentor architects and senior engineers
• Act as a trusted advisor to leadership and stakeholders

Skills Must have

• Microservices and event-driven architectures
• API management and integrations
• AWS Technologies
• Compute Containers
• Data Storage
• DevOps Automation
• Observability
• Security
• AWS CloudFormation / CDK / Terraform