Lead Full Stack Engineer, Enterprise AI Platform

DESCRIPTION & RESPONSIBILITIES

• Own the design and delivery of end-to-end experiences, from the backend services and data models that power them to the user-facing features built on top.
• Collaborate with Product and Design to translate business requirements into intuitive, high-quality user experiences, and evolve the underlying services and interfaces to support them.
• Define and evolve canonical data models, shared domain abstractions, and APIs (REST/GraphQL) that are scalable, intuitive, secure, and directly enable rich, data driven product experiences.
• Model and manage complex entity relationships, including graph-like structures and hierarchical data, and surface them through interfaces users can reason about.
• Build and maintain event-driven architectures (e.g., pub/sub, streaming) to support loosely coupled, extensible systems and responsive product behavior.
• Implement fine-grained access control patterns (RBAC/ABAC), ensuring secure and auditable data access across services and features.
• Design and integrate indexing and search capabilities (e.g., for retrieval, filtering, and AI use cases) and bring them into product experiences such as search, copilots, and recommendations.
• Integrate AI/ML capabilities into product workflows in a user-centric way, shaping both the underlying services and the surfaces users interact with.
• Shape the frontend architecture used across applications — framework choices, structure, conventions, state management, data fetching, performance, and accessibility — and apply it while building product features.
• Partner with Design to evolve the design system, and build and maintain the shared UI component libraries and frontend core modules that product features are composed from.
• Ensure reliability, scalability, and performance across services and user-facing features through observability, testing, and continuous iteration based on feedback and usage data.
• Drive developer experience improvements that increase velocity and consistency across teams, supporting other engineers in adopting and extending shared capabilities.
• Collaborate with DevOps and Security to implement secure and compliant patterns across the stack.
• Mentor engineers through design reviews, code reviews, and technical guidance within the team.

QUALIFICATIONS SERVICE / PERSONAL SKILLS:

• Strong systems thinker with a product mindset — able to design abstractions that scale across teams and use cases while staying grounded in user value and business impact.
• Clear communicator who can explain complex data models, APIs, and tradeoffs to technical stakeholders, and collaborate effectively with Product, Design, and Engineering partners.
• Highly collaborative, equally comfortable enabling other teams through well-designed shared capabilities and shipping end-to-end features cross-functionally.
• Execution-focused and pragmatic, with a strong sense of ownership over quality, reliability, and outcomes across the full stack.
• Curious and adaptable, especially in applying AI/LLM capabilities within structured data systems and real user workflows.

REQUIRED QUALIFICATIONS:

• 5 years of professional software engineering experience, with strong backend and full-stack capabilities.
• Proficiency in Python & TypeScript, with hands-on production experience in frameworks such as FastAPI or Django on the backend; React, Vue, or Angular — typically with a modern build tool such as Vite — on the frontend.
• Proven experience shipping user-facing products and features end-to-end, including the shared services, APIs, and data models that underpin them.
• Strong expertise in data modeling, including relational and non-relational patterns, and experience with graph or relationship-heavy domains.
• Deep experience designing, building, and consuming APIs (REST/GraphQL) and service-oriented architectures in product applications.
• Solid understanding of frontend architecture, state management, and performance optimization, with experience building intuitive interfaces on top of complex, datarich domains.
• Experience with event-driven systems (e.g., Kafka, Pub/Sub) and asynchronous processing patterns.
• Strong understanding of access control systems (RBAC, ABAC, multi-tenant design).
• Experience designing or integrating search and indexing systems (e.g., Elasticsearch, vector search).
• Solid experience with cloud-native systems (in particular the AWS ecosystem), CI/CD, and observability practices.
• Familiarity with AI/ML-enabled systems and integrating them into product experiences (e.g., RAG, entity resolution, semantic search, copilots, recommendations), including observability and evals for AI workflows, is a plus.
• Experience in data-rich domains (e.g., real estate, finance, asset management) is a plus.
• Embraces AI coding and actively leverages AI coding agents to augment day-to-day engineering work, treating fluency with these tools as a core part of the craft.
• Exercises strong judgment about when to trust agent output and when to review closely or take the wheel, with a clear sense of the failure modes of current models.
• Comfortable driving multiple agents in parallel on independent workstreams, orchestrating their work and integrating results efficiently.
• Continuously thinks about agent harness improvements — tooling, context, guardrails, feedback loops — that expand the autonomy and reliability of AI coding agents over time.

EDUCATION/DESIGNATIONS/LICENSES:

• Bachelor's degree in Computer Science, Software Engineering, or related technical field required (or equivalent practical experience).
• Advanced degree is preferred.
• Cloud certifications (e.g., AWS/Azure/GCP architecture or security certifications) are considered an asset.