Senior Principal Engineer

Senior Principal Engineer

Technical Lead / Architect, TechGrove AI Engineering Pod

You are the kind of engineer other engineers want to build with. You have spent your career going deep on production systems, and you have reached the point where your judgment shapes architectures, raises teams, and makes hard problems look simple. This is the most senior technical seat in the pod, and it is unapologetically hands-on.

As Technical Lead and Architect, you own the architecture for an OpCo’s modernized applications and set the engineering bar the whole pod builds to. You operate as a player/coach: designing complex systems, writing meaningful code, and running rigorous reviews of work produced by both engineers and AI agents. You treat agentic development as a first-class part of the architecture, not a novelty, and you define how the pod gets the most out of it without ever compromising quality or security.

If you want your decisions to matter, your code to ship, and your standards to lift an entire team, this is built for you.

A TechGrove AI Engineering Pod is a self-contained, AI-native software delivery team that we embed inside one of our Operating Companies (OpCos) to build, modernize, and ship production software. Each pod pairs senior engineering talent with agentic AI tooling such as Claude Code, plus the accelerators of Banyan’s AI Application Modernization Factory, to deliver at a velocity and quality bar a traditional team cannot match.

A pod is typically four to eight people, and OpCos add more pods as their ambitions grow. You will work as part of a tight, high-trust team with real ownership of what you build. Pods are delivered from Banyan’s India-based TechGrove.

• Own the architecture: Define and own the end-to-end software architecture for the pod’s applications, ensuring designs are scalable, secure, resilient, and cloud-native across AWS and Azure.
• Own the frontend architecture: Set the frontend architecture: state management, a scalable library of reusable components, design-system integration, and the patterns, standards, and performance budgets the pod builds against.
• Lead the technical direction: Serve as the highest technical authority and escalation point in the pod. Set design patterns and standards, and make confident architectural decisions amid ambiguity.
• Stay hands-on: Operate as a player/coach. Make significant code contributions, lead complex designs, and deliver thorough code reviews of work from both engineers and AI agents.
• Lead AI-native development: Define how the pod uses agentic tooling such as Claude Code across the SDLC, establishing patterns for AI-assisted design, implementation, testing, and review that maximize velocity while protecting quality and security.
• Set the quality bar: Define and enforce engineering excellence: clean code, Domain-Driven Design, modern design patterns, Twelve-Factor principles, meaningful test coverage, and application security.
• Build secure and reliable systems: Embed secure-by-design principles and cloud-native observability so applications run fast, stay available, and stay safe in production.
• Mentor and raise the team: Coach senior engineers, grow the technical capability of the team (human and agentic), and foster a culture of ownership and continuous improvement.
• Partner with the OpCo: Work with the OpCo’s technical leadership and existing teams to align architecture with their landscape, integrate with existing systems, and transfer knowledge.

• Experience: 10+ years in software engineering, with significant time in Principal Engineer, Staff Engineer, or Architect roles leading the architecture of complex, production systems.
• Production experience on BOTH AWS and Azure (required): You have personally designed, built, and run production software on both AWS and Azure. This dual-cloud depth is essential: you are the technical authority who sets cloud architecture regardless of which target cloud an OpCo runs on. Hands-on depth includes containers (Docker/Kubernetes), serverless (Lambda and Azure Functions), and Infrastructure-as-Code with Terraform.
• Architectural depth: Deep command of modern architectural patterns (microservices, event-driven, distributed systems), DDD, and design patterns, with a record of turning business objectives into technical solutions at enterprise or B2B scale.
• Hands-on technical depth: Current, real coding ability. A player/coach who contributes code, leads design, and delivers thorough reviews, including of AI-generated work.
• AI-native engineering: Demonstrated fluency with AI-assisted and agentic development tooling (Claude Code or similar) and a clear, practiced approach to architecting and delivering software in an AI-native team.
• Modern tech stacks: Hands-on production experience with at least two of: .NET Core, Python, TypeScript, and Java.
• Frontend architecture: Deep expertise in modern frontend architecture with React.js and Next.js: state management, scalable and reusable component design, design-system strategy, and frontend performance at scale.
• DevSecOps: Strong command of CI/CD (GitHub Actions, GitLab CI) and modern DevSecOps practices.
• Communication and leadership: You align technical and business stakeholders, lead under competing priorities, and bring calm and clarity to fast-moving teams.
• Education: Bachelor’s degree in Computer Science or a related technical field.

• Experience building and operating multi-tenant SaaS at scale.
• A track record leading application modernization or re-platforming of large enterprise or B2B applications.
• GenAI architecture experience: RAG and GraphRAG, LLM orchestration, multi-agent frameworks, MCP servers and tools, context engineering, and vector databases.
• Experience leading embedded or client-facing engineering teams.
• Working knowledge of GCP, in addition to AWS and Azure.

• First 90 days: You understand the OpCo’s landscape, have set the architectural direction and engineering standards, and the pod is shipping against them with a clean, AI-native workflow.
• First 6 months: The architecture is proven in production, quality and delivery metrics are trending up, and the team’s technical capability, human and agentic, has visibly grown under your leadership.

• 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.