Lead Software Engineer

The Phoenix Group; United States; On-site; USD 140,000 - 195,000; Full time

Job summary

The Phoenix Group is seeking an experienced Lead Full Stack Engineer to lead the design and delivery of an AI-first platform that transforms organizational knowledge into actionable insights. You will own backend services, data models, and frontend architecture, building end-to-end product experiences powered by modern APIs and AI capabilities.

You will collaborate with Product, Design, and Data teams to translate business needs into intuitive user experiences, establish scalable data models,

Qualifications

• Must design scalable data models and APIs
• Experience building end-to-end AI-enabled product features
• Strong backend and frontend architectural skills
• Proficient in relational and non-relational data modeling
• Experience with event-driven architectures and access control

Responsibilities

• Own end-to-end product experiences from backend to UI
• Translate business requirements into intuitive user experiences
• Define canonical data models and scalable APIs
• Model complex relationships and graph-like structures
• Build and maintain event-driven architectures and RBAC/ABAC
• Integrate AI/ML capabilities into product workflows
• Evolve frontend architecture and design systems
• Ensure reliability, performance, and observability across stack
• Mentor engineers and drive engineering velocity

Skills

Systems thinking

Clear communication

Collaborative

Ownership & accountability

AI/ML curiosity

Education

Bachelors in CS/SE

Advanced degree preferred

Tools

FastAPI

Django

React/Vue/Angular

Vite

Kafka

Elasticsearch/Vector search

AWS

CI/CD & observability

Job description

We are seeking a Lead Full Stack Engineer to help build and scale an AI-first platform that transforms organizational knowledge into actionable intelligence and enables smarter, faster decision-making.

This role is designed for a hands-on technical leader who operates across the full stack, shaping everything from the core services and data models that underpin applications to the user-facing features that bring them to life. You will design and build backend services, canonical data models, frontend architecture, design systems, and shared components used across multiple applications. You will also leverage these 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 throughout the delivery lifecycle, from foundational platform capabilities to the applications and features built on top of them. The ideal candidate combines strong systems design expertise with a product-oriented mindset and is equally comfortable defining durable technical abstractions and shipping polished, user-centric applications powered by modern APIs and AI capabilities.

Responsibilities

• Own the design and delivery of end-to-end product 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, evolving underlying services and interfaces to support changing needs.
• Define and evolve canonical data models, shared domain abstractions, and REST/GraphQL APIs that are scalable, intuitive, secure, and capable of enabling rich, data-driven product experiences.
• Model and manage complex entity relationships, including graph-like structures and hierarchical data, and expose them through interfaces that users can easily understand and navigate.
• Build and maintain event-driven architectures, including publish/subscribe and streaming systems, to support loosely coupled, extensible services and responsive product behavior.
• Implement fine-grained access control patterns, including role-based and attribute-based access control (RBAC/ABAC), ensuring secure and auditable data access across services and applications.
• Design and integrate indexing and search capabilities for retrieval, filtering, and AI-enabled use cases, incorporating them into product experiences such as search, copilots, and recommendations.
• Integrate AI and machine learning capabilities into product workflows with a strong focus on usability, reliability, and measurable business value.
• Establish and evolve frontend architecture across applications, including framework selection, project structure, engineering conventions, state management, data fetching, performance, and accessibility.
• Partner with Design to evolve the design system and develop and maintain shared UI component libraries and frontend core modules that accelerate product delivery.
• Ensure reliability, scalability, and performance across backend services and user-facing features through observability, automated testing, and continuous improvement informed by feedback and usage data.
• Drive developer experience improvements that increase engineering velocity and consistency across teams, enabling engineers to adopt and extend shared capabilities effectively.
• Collaborate with DevOps and Security teams to implement secure, reliable, and compliant engineering practices throughout the stack.
• Mentor engineers through architecture discussions, design reviews, code reviews, and ongoing technical guidance.

QUALIFICATIONS

Service / Personal Skills

• Strong systems thinker with a product mindset, capable of designing abstractions that scale across teams and use cases while remaining focused on user value and business outcomes.
• Clear communicator who can explain complex data models, APIs, architectural decisions, and technical tradeoffs to diverse stakeholders.
• Highly collaborative, with the ability to enable other teams through well-designed shared capabilities while also delivering end-to-end features across functional boundaries.
• Execution-focused and pragmatic, with a strong sense of ownership over quality, reliability, and outcomes across the full stack.
• Curious and adaptable, particularly in applying AI and large language model capabilities to structured data systems and real-world workflows.

Experience

• 5+ years of professional software engineering experience, with strong backend and full-stack development capabilities.
• Proficiency in Python and TypeScript, with hands-on production experience using backend frameworks such as FastAPI or Django and frontend frameworks such as React, Vue, or Angular, typically with a modern build tool such as Vite.
• Proven experience delivering user-facing products and features end-to-end, including the shared services, APIs, and data models that support them.
• Strong expertise in data modeling across relational and non-relational systems, with experience in graph-based or relationship-intensive domains.
• Deep experience designing, building, and consuming REST/GraphQL APIs and implementing service-oriented architectures for production applications.
• Solid understanding of frontend architecture, state management, and performance optimization, including the development of intuitive interfaces for complex, data-rich domains.
• Experience with event-driven systems, such as Kafka or cloud-based publish/subscribe services, and asynchronous processing patterns.
• Strong understanding of access control systems, including RBAC, ABAC, and multi-tenant application design.
• Experience designing or integrating search and indexing systems, including Elasticsearch and vector search technologies.
• Solid experience with cloud-native systems, particularly AWS, alongside CI/CD pipelines and observability practices.
• Familiarity with AI/ML-enabled systems and their integration into product experiences, including retrieval-augmented generation (RAG), entity resolution, semantic search, copilots, and recommendation systems. Experience with AI workflow observability and evaluation is an advantage.
• Experience working with data-intensive industries or domains, such as property, financial services, investment management, or enterprise analytics, is an advantage.
• Actively leverages AI coding assistants and agents to augment everyday engineering work, treating fluency with these tools as an essential part of modern software development.
• Demonstrates sound judgment in evaluating AI-generated code, understanding when to trust agent output, when to conduct deeper reviews, and when direct engineering intervention is necessary.
• Comfortable orchestrating multiple AI agents across independent workstreams and efficiently integrating their outputs into cohesive solutions.
• Continuously identifies opportunities to improve AI agent harnesses through better tooling, context management, guardrails, and feedback loops that increase agent autonomy and reliability over time.

Education / Designations / Licenses

• Bachelor's degree in Computer Science, Software Engineering, or a related technical discipline, or equivalent practical experience.
• Advanced degree preferred.
• Cloud certifications in architecture, engineering, or security across AWS, Azure, or Google Cloud are considered an asset.