Fullstack hands-on Architect R

We are seeking a hands-on Full Stack Architect who designs systems and builds them. This role owns the end-to-end architecture of cloud-native applications on the Golden Path engineering stack frontend backend services APIs data and cloud infrastructure while staying close to the code: writing production features building reference implementations and proofs of concept and setting the engineering bar through code and design reviews.

The ideal candidate is a senior engineer who grew into architecture without leaving the IDE equally comfortable whiteboarding a distributed system and debugging a React rendering issue or a slow gRPC call. They use AI-assisted engineering tools fluently in daily work and can architect AI-enabled features where they add real value while keeping the focus on sound scalable maintainable software.

Key Responsibilities

• Hands-On Engineering: Spend a significant portion of time writing production code across the stack ReactJS/TypeScript frontends and Go Java Python or (Koa) backend services; build reference implementations starter templates and proofs of concept that teams adopt.
• End-to-End Architecture: Own the architecture of full-stack applications UI composition API contracts (REST gRPC Thrift) service boundaries data models caching and integration patterns; document trade-offs through architecture decision records (ADRs).
• Cloud-Native Design on AWS: Design and build services on AWS (ECS Lambda API Gateway S3 Aurora/RDS CloudFront Route 53) using Docker Kubernetes Terraform and CI/CD (CircleCI) balancing scalability resilience security and cost.
• Distributed Systems & Modernization: Lead monolith-to-microservices decomposition into well-bounded services; apply event-driven patterns (Kafka EventBridge SQS) and workflow orchestration (Temporal Airflow) where they fit.
• Engineering Excellence: Drive quality through design reviews pull request reviews and pairing; establish testing strategy (unit integration API Cypress-based UI regression) observability (Datadog CloudWatch OpsGenie) and secure coding practices.
• Production Ownership: Troubleshoot complex production issues across layers frontend performance API latency database bottlenecks and infrastructure and lead root-cause analysis and remediation.
• AI Fluency: Use AI-assisted engineering tools (Claude Code GitHub Copilot Gemini) to accelerate delivery and guide teams on using them responsibly; architect AI-enabled features (LLM integration RAG agent workflows) when the product calls for them.
• Technical Leadership & Collaboration: Mentor lead and senior engineers; partner with product managers designers and client stakeholders to turn requirements into buildable designs and communicate decisions risks and trade-offs clearly.

Required Skills & Experience

Technical Experience

• Bachelors degree in Computer Science Software Engineering or equivalent with 10 years of software engineering experience including 3 years in an architect or technical lead role while remaining hands-on.
• Deep frontend expertise in ReactJS TypeScript and JavaScript (hooks functional components state management performance tuning) building large-scale high-performance UIs.
• Strong backend expertise in at least two of Go Java Python or building APIs and microservices with REST gRPC and Thrift (Koa experience a plus).
• Solid grounding in system design and distributed systems scalability resiliency consistency caching performance optimization and failure handling.
• Experience with relational and NoSQL databases (PostgreSQL MySQL Aurora RDS DynamoDB MongoDB Redis) including data modeling and query performance.
• Strong AWS experience (ECS Lambda API Gateway S3 IAM CloudFront Route 53 Aurora/RDS) plus Docker Kubernetes Terraform and CI/CD pipelines.
• Experience defining and implementing testing strategy (Jest Cypress API/integration testing) and observability (Datadog CloudWatch OpsGenie).
• Strong grasp of networking and security fundamentals DNS authentication/authorization (OAuth OIDC) encryption and secure API design.
• Daily practical use of AI-assisted engineering tools (Claude Code GitHub Copilot Gemini) and a working understanding of how to integrate LLM capabilities into applications.

Professional Skills

• Proven track record of designing and personally building complex full-stack systems from concept to production.
• Strong analytical problem-solving and debugging skills across the full stack.
• Ability to balance architectural rigor with pragmatism choosing the simplest design that meets business delivery and operational needs.
• Excellent communication skills with the ability to explain technical decisions to engineers product leaders and client stakeholders.
• Mentoring mindset with a track record of raising the technical bar of the teams around them.

Nice to Have Skills

• Experience with event-driven and workflow platforms (Kafka EventBridge Temporal Airflow) and data platforms such as Databricks.
• Experience with Elasticsearch or other high-scale search and indexing platforms.
• Experience building enterprise design systems or shared UI component libraries.
• Familiarity with monorepos and build systems such as Bazel.
• Hands-on experience building GenAI features with AWS Bedrock Azure OpenAI or OpenAI APIs (RAG tool use agent orchestration).
• Exposure to high-scale SaaS marketplace PropTech or customer-facing digital product platforms.
• AWS Solutions Architect or equivalent cloud certification.

Know more about PPE: what its like to work and grow at Brillio: Employment Opportunity Declaration

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