Lead Full Stack Engineer, Enterprise AI Platform
New York, NY, 10001
Reference ID: 33187528
Date Posted: 10/04/2026
Job Title: Lead Full Stack Engineer, Enterprise AI Platform
Location-Type: Hybrid NYC, NY
Start Date Is: ASAP
Duration: (contract, perm, etc) FTE Perm
Compensation Range: $200-250k/yr bonus benefits
Benefits: Eligible for Health, Dental, Vision, 401K, PTO
Must be authorized to work in the U.S. This position is not eligible for sponsorship.
DESCRIPTION & RESPONSIBILITIES
Our client is seeking a Lead Full Stack Engineer to help build and scale an AI-first platform that amplifies the company's intelligence and enables smarter decisions, faster.
This role is for a hands-on technical leader who operates across the full stack, shaping everything from the core services and data models that underpin our applications to the user-facing features that bring them to life. You will design and build backend services, canonical data models, and the frontend architecture, design system, and shared components used across our applications — and you will use those same foundations to deliver end-to-end, AI-powered product experiences that translate complex data into intuitive, high-impact workflows.
You will partner closely with Product, Design, and Data teams across the full arc of delivery, from foundational capabilities through the features built on top of them. The ideal candidate combines strong system design skills with a product mindset, and is equally comfortable defining durable abstractions and shipping polished, user-centric applications powered by modern APIs and AI capabilities.
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.
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