Senior Full-Stack Engineer

Position Summary

The company’s AI Application Development team is a fast-moving group that builds AI-enabled applications and agents for the business. The team runs like a startup with enterprise backing: a senior engineer typically owns an application from the first business conversation through production, and there is a deep backlog of projects waiting for the right people.

We are seeking a Senior AI Full Stack Engineer who is, first and foremost, a strong developer. You will take a project from intake, work cross-functionally to gather and shape requirements, design and build the full stack with AI-assisted development tools, and carry it through CI/CD into production — applying sound application governance at every step. This role suits an engineer who enjoys owning outcomes, working directly with business stakeholders, and shipping reliable software quickly.

Key Responsibilities

Own Projects End to End

•     Take ownership of new applications and features from intake through production, typically as the lead senior engineer on the project.

•     Partner with business stakeholders, product owners and other technology teams to gather requirements, clarify the business case and agree on scope and priorities.

•     Translate requirements into a technical design: front-end and back-end split, data model, API contracts and integration points, with clear reasoning for key choices.

•     Keep stakeholders informed with clear, concise updates; surface risks, trade-offs and decisions early.

Build Full-Stack Applications

•     Build modern web applications with TypeScript / JavaScript, React and Next.js on the front end and Node.js on the back end, using Prisma and PostgreSQL for data access.

•     Design and build RESTful and GraphQL APIs and services, and integrate enterprise systems and data sources such as Salesforce, Snowflake and internal APIs.

•     Implement secure authentication and authorization, including Microsoft Entra ID SSO, OAuth 2.0 and role-based access.

•     Build in-house applications that replace costly or ill-fitting vendor platforms, delivering measurable business value.

AI-Assisted Development & AI Features

•     Use AI coding tools such as Claude Code, Cursor and Codex daily, with a disciplined workflow: rules files, skills or slash commands, planning and review steps that keep AI-generated code to standard.

•     Review, refactor and harden AI-generated code for production: security, performance and maintainability.

•     Build AI features into applications, including LLM integrations, agents, retrieval-augmented generation (RAG) and MCP connectors, with guardrails that keep company and customer data safe.

•     Operate within the team’s AI-assisted development workflow (Lovable > GitHub > Claude Code > Harness > Azure/Vercel).

Development to Production (CI/CD)

•     Take applications from development into production through CI/CD pipelines in GitHub and Harness: automated builds and tests, quality and security checks, environment promotion, approvals and rollback.

•     Work with Platform Engineering on hosting, deployment and the path to production on Azure, including containers and the Kong API gateway.

•     Own applications after launch: monitor with Dynatrace, troubleshoot production issues and iterate based on usage and feedback.

Application Governance & Quality

•     Apply application governance throughout the lifecycle: code review, testing standards, secure coding, secrets management, dependency and vulnerability scanning, and documentation.

•     Follow and help shape the AI Center of Excellence’s architecture, coding and AI-usage standards, including data protection and responsible use of AI.

•     Maintain clear technical documentation, decision records and runbooks so applications can be supported and extended by others.

Team Enablement

•     Build reusable components, services, templates and patterns that help other engineers deliver faster and more consistently.

•     Share AI-assisted development practices, mentor junior engineers and contribute to code-review and engineering standards.

Required Qualifications

•     5+ years of professional software development, including 3+ years building full-stack applications and owning them through to production.

•     Strong proficiency in JavaScript / TypeScript, React (Next.js preferred) and Node.js. Engineers with deep experience in another modern back-end language (such as Go, Java or Python) and a clear plan to ramp on Node.js are considered.

•     Experience with relational databases (PostgreSQL preferred; Prisma or similar ORM) and NoSQL data stores.

•     Strong API and service design (REST, GraphQL, microservices) and experience integrating third-party and enterprise systems.

•     Proven experience gathering requirements directly with business stakeholders and working cross-functionally with product, business and technology teams.

•     Solid understanding of CI/CD: automated testing, build and deployment pipelines, environment promotion and rollback (Harness, GitHub Actions, Jenkins or similar).

•     Practical application governance: code review, unit and integration testing, secure coding, authentication and authorization (OAuth 2.0 / JWT / SSO), secrets management and documentation.

•     Daily, hands-on use of AI coding assistants (Claude Code, Cursor, Codex or GitHub Copilot) with a repeatable workflow and clear practices for verifying AI-generated code.

•     Hands-on cloud experience (Azure preferred; AWS considered), including containerized applications.

•     Clear, concise communication: you can explain designs and trade-offs to technical and business audiences and back up results with numbers.

Preferred Qualifications

•     Experience building AI features in production: LLM APIs (Azure OpenAI, Claude, AWS Bedrock), agents and orchestration (LangChain or similar), RAG and guardrails.

•     Experience building or integrating MCP servers and connectors.

•     Familiarity with Supabase, pgvector, Snowflake or Salesforce integrations.

•     Working knowledge of Docker and Kubernetes, infrastructure as code (Terraform), API gateways (Kong) and observability tools (Dynatrace).

•     Experience with additional languages or platforms such as Python, Go, Java or mobile (Flutter / React Native).

•     Experience building internal enterprise applications or replacing vendor SaaS platforms with in-house solutions.

•     Experience mentoring engineers or leading small project teams.

•     Bachelor’s degree in Computer Science or a related field, or equivalent experience.

Core Tools & Technologies

Front End

TypeScript / JavaScript, React, Next.js

Back End & Data

Node.js, Prisma, PostgreSQL, REST / GraphQL; some Python FastAPI; Supabase

AI-Assisted Development

Claude Code, Cursor, Codex, GitHub Copilot

AI

Claude, Gemini, Azure OpenAI; agents; MCP connectors; RAG

CI/CD & Source Control

GitHub, Harness

Cloud & Platform

Azure (primary), containers / Kubernetes (run by Platform Engineering), Kong API gateway

Security & Observability

Microsoft Entra ID, Dynatrace