Solution Architect

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

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:

Microservices and event-driven architectures

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:

Amazon SageMaker

Amazon Bedrock (LLMs & foundation models)

AWS Glue, Lake Formation

Hands-on experience with:

LLM-based architectures and agent-based systems

AI observability tools (e.g., OpenTelemetry, Langfuse, Prometheus/Grafana)

Prompt lifecycle management and evaluation pipelines

Strong understanding of:

AI governance frameworks and enterprise AI controls

Agent orchestration, monitoring, and guardrails

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

Other

Languages

English: C1 Advanced

Seniority

Senior