Full Stack Enterprise Solutions Architect

Job Description

Job Description

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