Senior AI Engineer (f/m/d)

What you will do

Design & Develop: Architect and implement end-to-end AI Agents and full-stack applications that automate complex business processes.

Foundational Engineering: Build and maintain the core AI tech stack, including agent orchestration frameworks, vector database integrations, and RAG (Retrieval-Augmented Generation) pipelines.

Cloud Orchestration: Oversee the deployment and management of scalable AI services, selecting and adapting infrastructure to meet stringent requirements for high availability, performance, and efficiency.

Strategic Transformation: Act as a key contributor to Sonar’s AI transformation, identifying high-impact opportunities for agentic automation across different departments.

Governance & Ethics: Collaborate with cross-functional teams to establish governance, security protocols, and best practices for AI development and data privacy.

Full-Stack Ownership: Manage the entire lifecycle of internal tools, from backend logic and LLM prompt engineering to intuitive frontend interfaces for internal users.

Mentorship: Guide junior engineers and contribute to a culture of technical excellence in AI and automation.

Experience and qualifications

Full-Stack Expertise: 5+ years of professional experience in full-stack development (e.g., Python, Node.js , React, or similar modern stacks).

AI Agent Mastery: Proven experience developing and deploying autonomous AI Agents using frameworks such as LangChain, AutoGen, CrewAI, or similar.

Automation Roots: A strong background in traditional automation development (e.g., scripting, workflow engines, or RPA) prior to the LLM era, demonstrating a deep understanding of logic-based systems.

Cloud Proficiency: Hands-on experience architecting and deploying production-grade applications on any major cloud platform (AWS experience is highly recommended).

Architectural Vision: Deep understanding of the specific architectures required for agentic workflows, including state management, tool-calling, and memory systems.

Data & AI Skills: Experience with vector databases (e.g., Pinecone, Weaviate), fine-tuning (optional but preferred), and advanced prompt engineering.

Collaborative Mindset: Ability to work with non-technical stakeholders to define governance and translate business needs into technical requirements.

Growth Mindset: A passion for staying at the forefront of AI research and a desire to continuously evolve your skill set.

Salary range