Full stack Enterprise Solution Architect

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

• 8+ years of experience in software development and solution architecture
• Strong full-stack expertise (modern JavaScript frameworks, backend services, APIs, and databases)
• Proven experience designing enterprise-scale, high-reliability systems
• Deep understanding of cloud platforms (AWS, Azure, or Google Cloud Platform) and distributed architectures
• Experience with microservices, REST/GraphQL APIs, messaging, and integration patterns
• 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