Principal Software & AI Engineer

Overview

We are seeking a Principal Software & AI Engineer to act as a technical leader across the full delivery lifecycle — from shaping solutions with customers to building, deploying, and operating them in production. You combine deep fullstack engineering expertisewith hands-on AI engineering capabilities and a strong DevOps foundation. Equally comfortable in front of a whiteboard with a client and deep in a codebase, you translate business problems into robust, scalable architectures, lead by example on technical quality, and mentor engineers across teams. This is a hands-on principal role: you set technical direction, drive solutioning, and remain close to the code.

Key Responsibilities

• Architect and build fullstack applications end to end, from modern web frontends through backend services, APIs, and data layers.

• Design, develop, and operationalize Generative AI capabilities — including LLM-based solutions, RAG pipelines, prompt and context engineering, model integration, evaluation, and guardrails — and embed them into production applications.

• Lead technical solutioning in collaboration with customers: gather requirements, shape architectures, scope and estimate work, and present technical proposals and trade-offs to both technical and business stakeholders.

• Own the DevOps lifecycle — CI/CD, infrastructure-as-code, containerization, orchestration, and observability — ensuring secure, reliable, and repeatable delivery.

• Set and uphold engineering standards across architecture, code quality, testing, and security.

• Mentor and coach engineers, lead technical reviews, and grow capability across the team.

• Act as a trusted technical advisor to clients, supporting pre-sales and discovery alongside delivery.

Required Skills & Experience

• Extensive fullstack engineering experience. The specific stack is open, but you must be highly proficient with modern frameworks on both frontend (e.g. TypeScript with React or Angular) and backend (e.g. Python, Node.js, Java, or .NET).

• Demonstrated AI engineering experience: building and shipping production Generative AI solutions, working with LLMs, embeddings/vector stores, RAG, orchestration frameworks, and model evaluation and monitoring.

• Strong DevOps background: CI/CD, infrastructure-as-code (e.g. Terraform / Bicep), Docker, Kubernetes, and hands-on experience with Microsoft Azure (mandatory — our primary cloud platform).

• Proven technical consulting and pre-sales experience: directly engaging customers, leading solutioning and architecture discussions, supporting discovery and pre-sales, and communicating clearly with both engineers and business stakeholders.