Full Stack Developer / AI Focused

AI-Forward Deployment

• Deploy LLM-powered features and workflows from use-case identification through production delivery.
• Integrate LLM APIs and AI frameworks into search, summarization, recommendations, automation, and decision support.
• Validate AI-generated outputs, use coding assistants, and evaluate emerging models, frameworks, and techniques.

Collaboration and Communication

• Partner with Marketing, Customer Experience, Data Science, Merchandising, Warehouse Operations, Finance, Supply Chain, Product, and Security.
• Translate technical concepts for non-technical stakeholders and present project outcomes and architectural decisions.
• Write documentation, run team demos, and mentor peers.

Required Qualifications

• Three to six years of professional software engineering experience in a production environment, with systems owned and shipped.
• Strong proficiency in one or more of Python, Java, TypeScript, Go, or C#.
• Knowledge of object-oriented programming, SOLID principles, design patterns, and maintainable architecture.
• Experience with relational databases, at least one NoSQL store, RESTful APIs, testing, cloud platforms, Docker, CI/CD, and Git.
• Experience using AI coding assistants and integrating at least one LLM-powered feature or workflow.
• Understanding of prompt design, structured LLM outputs, and critical evaluation of AI results.

Preferred Qualifications

• Experience with RAG pipelines, vector databases, AI orchestration frameworks, observability, and monitoring tools.
• Background in microservices, event-driven systems, security best practices, Agile/Scrum, or open-source contributions and public portfolios.

Technology Landscape

• Languages include Python, TypeScript, Java, Go, and SQL.
• Databases and data tools include PostgreSQL, MySQL, MongoDB, Redis, DynamoDB, pgvector, dbt, Airflow, and Spark.
• Cloud and infrastructure tools include AWS, GCP, Azure, Docker, Kubernetes, and Terraform.
• APIs and delivery tools include REST, GraphQL, gRPC, OpenAPI, GitHub Actions, ArgoCD, Jenkins, and CircleCI.
• AI and observability tools include OpenAI, Anthropic Claude, Gemini, GitHub Copilot, Cursor, Claude Code, Datadog, OpenTelemetry, Prometheus, and Grafana.
• Kafka is included in the technology landscape for data and event-driven systems.

Working Style