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