Description :

Position Overview :

The Senior AI Engineer is a technical leader driving InvoiceClouds generative AI strategy from concept to scalable production. This role owns the architecture, governance, and delivery of AI and LLM-powered capabilities, ensuring measurable business outcomes, platform reliability, and long-term AI maturity.

You will operate at the intersection of AI innovation, engineering rigor, and product strategy while mentoring engineers and influencing cross-functional stakeholders.

Key Responsibilities :

Strategic Impact :

- Lead end-to-end development and deployment of scalable AI/ML and generative AI solutions.

- Define and track KPIs for scalability, latency, accuracy, cost, and reliability.

- Translate business strategy into executable AI roadmaps and technical designs.

Technical Leadership & Ownership :

- Act as a subject matter expert for AI architecture, frameworks, and model lifecycle management.

- Establish reusable AI patterns, standards, and governance practices.

- Lead MLOps implementation including monitoring, observability, and automated retraining.

- Ensure data governance, security, and compliance across AI systems.

Innovation & Architecture :

- Evaluate and prototype advanced AI technologies including agentic frameworks and multimodal AI.

- Drive platform-level adoption of Azure OpenAI, LangChain, Semantic Kernel, and vector-based architectures.

- Optimize inference pipelines for performance, scalability, and cost efficiency.

Customer & Business Alignment :

- Design AI-powered experiences that enhance personalization and customer engagement.

- Partner with AI Product Strategy, Sales, and Customer Success to support go-to-market initiatives.

- Champion responsible AI with a focus on trust, transparency, and explainability.

Mentorship & Collaboration :

- Mentor AI Engineers and elevate engineering standards across teams.

- Collaborate closely with Product, Data Science, Platform, and Executive leadership.

Required Qualifications :

- 7 to 12 years of software engineering experience, including 35+ years building AI/ML or LLM-powered systems.

- Proven experience delivering production-grade AI solutions in SaaS environments.

- Deep expertise in Python and C#, Azure OpenAI, Semantic Kernel, LangChain, FastAPI, and vector databases.

- Strong understanding of model evaluation, prompt tuning, inference optimization, and AI observability.

- Experience defining AI architecture, governance, and best practices.

- Excellent leadership, stakeholder management, and communication skills.