Senior Full-stack Engineer - (Cloud, AI)

Experience: Strong software engineering experience building production applications.

Production experience on AWS or Azure (required): You have built and run production applications on AWS or Azure. Experience limited to GCP alone does not meet this requirement, although GCP in addition to AWS or Azure is a plus.

Full-stack ability: Strong proficiency across the stack: modern backend languages and modern UI frameworks (React.js, Next.js, Vite).

Modern tech stack: Strong, hands-on experience with at least one of: .NET Core, Python, TypeScript, or Java.

Frontend and design systems: Solid hands-on React.js experience: building responsive, accessible UIs from reusable components, managing client-side state, and working within an established design system and component library.

APIs and data: Hands-on experience designing APIs (REST and/or GraphQL) and working with SQL and No-SQL databases.

IaC and DevSecOps: Experience with Infrastructure-as-Code (Terraform) and building and maintaining CI/CD pipelines (GitHub Actions, GitLab CI).

AI-native tooling: Fluency with AI-assisted development tooling (Claude Code or similar) as a core part of daily work.

Engineering principles: Solid grounding in DDD, clean code, SOLID and DRY, test-driven development, strong typing, and code hygiene.

Problem solving: Structured technical problem-solving (decomposition, hypothesis-driven testing) to debug complex issues in distributed systems.

Agile and ownership: Experience working in Agile (Scrum/Kanban) with a proactive ownership mindset.

Containerization (Docker/Kubernetes) and serverless (AWS Lambda, Azure Functions).

Experience developing GenAI capabilities (LangChain, LlamaIndex) or multi-agent frameworks (crewAI, AutoGen).

Message queuing and streaming technologies (Kafka, RabbitMQ).

Experience with SaaS operating models and observability / APM tooling.

Experience with application modernization or re-platforming.

Working knowledge of GCP, in addition to AWS or Azure.

First 90 days: You are shipping production features independently, your code sets a clean example for the pod, and you are using agentic tooling fluently in your daily workflow.

First 6 months: You are trusted with complex, cross-cutting features, you raise quality through reviews and patterns, and you are a dependable engine of the pod’s delivery.

Permanent home, long-term thinking: Banyan acquires great software businesses and keeps them for good. We invest for the long term, which means you build software meant to last, not to flip.

Real ownership: You own outcomes end to end inside a small, senior team. The OpCo owns the “what”; the pod owns the “how.”

AI-native by default: You work every day with agentic tooling and the AI Application Modernization Factory, not as a side experiment but as the core of how we build.

Variety with stability: Pods work across a portfolio of real products and domains, so you keep learning, with the security of a permanent employer behind you.

Growth and excellence: A Banyan Director of Engineering Excellence supports every pod with coaching, standards, and continuous improvement, so your craft compounds over time.

We have written this role to be honest about what it takes, not to describe a mythical perfect candidate. If you meet most of what is listed and you are excited by the work, we want to hear from you. Strong engineers grow into the rest, and we will help you do exactly that.

We are building diverse, inclusive teams, and we welcome applicants of every background. What matters most is the quality of your engineering, your curiosity about AI-native development, and your appetite to own outcomes.

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