We are seeking an experienced Full Stack Enterprise Solution Architect to design and guide the development of mission-critical technology solutions supporting investment management, research, trading, risk, and operational workflows. This role plays a key part in modernizing and evolving enterprise platforms while maintaining the stability, security, and governance required in a regulated financial environment. This role bridges architecture strategy and technical execution, working closely with stakeholders, engineering teams, and leadership to translate complex requirements into robust, future-proof architectures.
The ideal candidate combines deep hands-on technical expertise with strong architectural judgment, communication skills, and a pragmatic approach to enterprise systems, along with an appreciation for the unique constraints of asset management systems—data accuracy, auditability, resilience, and long-term maintainability.
Key Responsibilities
· Lead the end-to-end architecture of enterprise applications, spanning front-end, back-end, integration, data, and cloud infrastructure
· Partner with business (portfolio managers, analysts, operations, compliance), and technology stakeholders to understand requirements and translate them into scalable technical platform solutions
· Define and enforce architecture standards, patterns, and reference architectures
· Design APIs, microservices, event-driven systems, and integration layers to support enterprise workflows
· Evaluate and recommend technologies, platforms, and vendors aligned with long-term strategy
· Provide hands-on guidance and technical leadership to development teams
· Ensure solutions meet regulatory, security, performance, reliability, data governance and compliance requirements
· Review solution designs, code, and deployments to ensure architectural integrity
· Support cloud and hybrid architectures, including scalability, resilience, and cost optimization
· Mentor other solution architects / developers and help raise overall engineering and architectural maturity
Required Qualifications
· 10 years of experience in software development and solution architecture
· 5 years of full-stack expertise (modern JavaScript frameworks, backend services, APIs, and databases)
· 5 years of experience designing enterprise-scale, high-reliability systems
· 5 years of cloud platforms (AWS, Azure, or GCP) and distributed architectures
· 5 years of experience with microservices, REST/GraphQL APIs, messaging, and integration patterns
Preferred Qualifications
· Solid grounding in security principles, authentication/authorization, and data protection
· Strong communication skills with the ability to explain complex technical concepts to non-technical audiences
· Experience in asset management, investment management, banking, or financial services, or large enterprise environments
· Familiarity with DevOps, CI/CD pipelines, and infrastructure-as-code
· Experience with containerization and orchestration (Docker, Kubernetes)
· Exposure to data platforms, analytics, or event streaming technologies
· Experience with enterprise AI platforms (ChatGPT Enterprise, Copilot Studio, Gemini, Snowflake Cortex AI) and AI application use cases
· Background in regulated industries for compliance awareness.
· Prior experience mentoring engineers or leading architectural reviews
Technical Skill breakdown
Backend Development
.NET Core / .NET 6+: Expertise in building scalable APIs and microservices.
C#: Strong command of asynchronous programming, LINQ, and design patterns.
API Design: RESTful and GraphQL services for integration.
Frontend Development
JavaScript/TypeScript: Advanced proficiency.
Frameworks: React.js, Angular, or Vue.js for responsive UI design.
UI/UX: Accessibility standards, component-based architecture, and state management.
Database & Data Engineering
Snowflake: Deep understanding of data warehousing, SQL optimization, and integration with AI workflows.
Familiarity with dbt for transformations and Azure SQL as fallback
AI & Emerging Tech Integration
Generative AI & LLMs: Experience with OpenAI, Claude, Gemini, and Azure OpenAI for building intelligent features.
Prompt Engineering: Crafting effective prompts for AI-driven workflows.
Agentic Architecture: Implementing Retrieval-Augmented Generation (RAG), embeddings, and vector search for AI agents.
Model Orchestration: Deploying and integrating models from Hugging Face, Vertex AI, or OpenAI APIs
Cloud & DevOps
Cloud Platforms: Azure expertise (App Services, Functions, Identity & Security).
CI/CD Pipelines: GitHub Actions, Jenkins for automated deployments.
Containerization: Docker and Kubernetes for scalable deployments.
Security: OAuth, DLP, encryption (Double Key Encryption), and compliance with InfoSec standard
Model & AI Governance
Understanding of data protection policies, secure credential management, and governance frameworks for AI integration