Solution Architect

Project description

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: o Component-level services (microservices, APIs) o 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: o RAG (Retrieval-Augmented Generation) o Feature stores and data pipelines o Model deployment, versioning, and scaling AI Governance, Observability & Control
• Define and implement enterprise AI governance frameworks covering: o Responsible AI usage (fairness, bias mitigation, explainability) o Data privacy, lineage, and compliance o AI risk classification and policy enforcement
• Establish AI observability and monitoring capabilities, including: o End-to-end tracing of AI/ML and LLM flows using tools such as OpenTelemetry o Monitoring of prompts, responses, latency, and model behavior using platforms like Langfuse or equivalent o Metrics for model performance, drift, hallucination rates, and usage patterns
• Design and enforce agent governance and control mechanisms, including: o Monitoring and auditing of autonomous and semi-autonomous AI agents o Guardrails for agent behavior, tool usage, and decision boundaries o Human-in-the-loop (HITL) workflows and escalation patterns o Policy-based control over agent actions and integrations
• Implement AI lifecycle governance, including: o Model validation, approval workflows, and audit trails o Continuous evaluation and feedback loops o 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

• Core Architecture
• 8-12+ years in software engineering and architecture roles
• Proven experience designing large-scale distributed systems
• Knowledge of .NET and/or Python
• Strong knowledge of: o Microservices and event-driven architectures o API management and integrations AWS Technologies Compute & Containers
• Amazon EC2, AWS Lambda
• Amazon ECS / EKS (Kubernetes) Networking & Integration
• Amazon VPC, Route 53, API Gateway
• AWS App Mesh, EventBridge, SNS, SQS Data & Storage
• Amazon S3, EBS, Glacier
• Amazon RDS, Aurora, DynamoDB, Redshift DevOps & Automation
• AWS CloudFormation / CDK / Terraform
• AWS CodePipeline, CodeBuild, CodeDeploy Observability
• Amazon CloudWatch, AWS X-Ray Security
• AWS IAM, Cognito, KMS, Secrets Manager
• AWS Organizations and Control Tower AI/ML, LLM & Observability Expertise
• Experience with AWS AI/ML stack: o Amazon SageMaker o Amazon Bedrock (LLMs & foundation models) o AWS Glue, Lake Formation
• Hands-on experience with: o LLM-based architectures and agent-based systems o AI observability tools (e.g., OpenTelemetry, Langfuse, Prometheus/Grafana) o Prompt lifecycle management and evaluation pipelines
• Strong understanding of: o AI governance frameworks and enterprise AI controls o Agent orchestration, monitoring, and guardrails o Data lineage, quality, and compliance Architecture Frameworks & Practices
• TOGAF or equivalent enterprise architecture frameworks
• Domain-driven design (DDD)
• Cloud-native and serverless patterns
• Experience integrating data, semantic, and ML architecturesSoft Skills
• Strong communication and stakeholder management
• Strategic thinking with hands-on technical depth
• Ability to influence senior leadership and cross-functional teams
• Mentorship and leadership capabilities

Nice to have

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