Lead Full Stack Engineer

Role Overview

This position offers a leadership role in designing and building scalable full stack systems, encompassing backend services, data models, and frontend architectures that support complex, data-driven product experiences. The candidate will operate as a hands-on technical leader, influencing core services and delivering end-to-end applications that leverage AI capabilities for enterprise insight and operational efficiency.

Key Responsibilities

• Lead the design, development, and deployment of full stack applications, including backend services, APIs (REST/GraphQL), and frontend interfaces, ensuring modularity, security, and high performance.
• Collaborate with cross-functional teams—Product, Design, Data Science—to translate requirements into intuitive, reliable user experiences and scalable backend solutions.
• Define and evolve canonical data models, manage complex entity relationships (graphs, hierarchies), and develop indexing/search solutions (Elasticsearch, vector search) supporting AI-driven search and recommendation features.
• Build event-driven architectures (Kafka, cloud pub/sub), implementing asynchronous workflows and stream processing for scalable, real-time data handling.
• Integrate AI/ML functionalities—such as retrieval-augmented generation (RAG), semantic search, and entity resolution—into workflows, optimizing usability and business impact.
• Establish frontend architecture using modern frameworks (React, Vue, Angular) with focus on performance, accessibility, and shared UI component libraries.
• Drive service reliability, system observability, automated testing, and continuous improvement practices.
• Implement robust security measures, including role-based (RBAC) and attribute-based access controls (ABAC), across all layers of the application stack.
• Mentor engineering teams in architecture, code quality, and technical innovation, fostering best practices and engineering excellence.
• Coordinate with DevOps and Security to ensure compliant, scalable, and resilient infrastructure, primarily on cloud platforms like AWS.

Core Qualifications & Requirements

• 5+ years of professional full stack software engineering, with demonstrated leadership in complex enterprise systems.
• Strong expertise in backend frameworks (FastAPI, Django) and frontend frameworks (React, Vue, Angular) with modern build tools (Vite).
• Proficiency in Python and TypeScript; solid understanding of data modeling (relational, NoSQL, graph databases).
• Extensive experience designing and consuming RESTful and GraphQL APIs, with large-scale, service-oriented architecture knowledge.
• Hands-on experience with event-driven systems (Kafka, cloud pub/sub) and asynchronous processing pipelines.
• Skilled in implementing security controls (RBAC, ABAC) and multi-tenant applications, with familiarity in search technologies (Elasticsearch, vector search).
• Deep understanding of cloud-native development in AWS; CI/CD, observability, and automation practices.
• Familiarity with AI/ML feature integration, including retrieval-augmented generation (RAG), semantic search, and AI workflow observability.
• Ability to translate technical solutions into scalable, business-oriented products and collaborate across multidisciplinary teams.

Nice-to-Have Qualifications

• Advanced degree in Computer Science, Software Engineering, or related fields; relevant cloud certifications (AWS, Azure, GCP).
• Experience in data-intensive industries such as finance, property management, or enterprise analytics.
• Active use of AI coding assistants and agents, with an understanding of their application in modern software development workflows.
• Knowledge of search optimization and domain-specific data modeling within complex enterprise environments.

Core Technical Skills

• Backend: Python, FastAPI, Django
• Frontend: React, Vue, Angular, Vite, JavaScript/TypeScript
• APIs: REST, GraphQL
• Databases: Relational (PostgreSQL, MySQL), NoSQL, Graph databases
• Event systems: Kafka, cloud pub/sub (AWS SNS/SQS)
• Search: Elasticsearch, vector search, retrieval systems
• Cloud: AWS (S3, EC2, Lambda, CloudWatch)
• AI/ML: Retrieval-augmented generation (RAG), semantic search, entity resolution, AI integrations
• Security: RBAC, ABAC, multi-tenancy
• DevOps: CI/CD pipelines, observability, automation

Career Impact

Join a forward-thinking organization driving innovation in knowledge automation through AI, where your leadership will directly influence the development of impactful enterprise solutions.

Compensation and Benefits

Competitive salary commensurate with experience, comprehensive benefits package, and flexible remote work options aligned with EST working hours. Occasional travel (2-3 times per year) is expected.