Lead AI Solutions Engineer

TEKNIKOZ; Bayern; Vor Ort; EUR 90.000 - 130.000; Vollzeit

Zusammenfassung

TEKNIKOZ is seeking a Lead AI Solutions Engineer to join our IT Services team for a global manufacturing client. The role focuses on strategic execution, blueprinting, and bridging business goals with robust AI architectures across GenAI, Agentic AI, and traditional ML.

You will lead hands-on development, design scalable solutions, and ensure secure experimentation on Azure and Databricks, delivering production-grade AI applications. 10–15 years of experience is required.

Qualifikationen

• 10–15 years of AI/ML experience.
• Ability to translate strategic goals into technical architectures and roadmaps.
• Hands-on development and deployment across GenAI, Agentic AI, and traditional ML on Azure/Databricks.

Aufgaben

• Synthesize strategic goals into architectures, roadmaps, and execution plans.
• Define end-to-end AI lifecycles from PoC to production deployment.
• Evaluate AI requests and guide feasibility, ROI, risk and outcomes.

Kenntnisse

AI strategy

Machine learning

Generative AI

Agentic AI

Azure

Databricks

Tools

Azure

Databricks

Jobbeschreibung

Please Note: Only GC Profiles are required. No other Visas will work.

Position Overview

We are seeking a technical and consultative Lead AI Solutions Engineer with 10 to 15 years of experience to join our IT Services team for a global manufacturing client. In this high-impact role, you will act as the strategic right-hand to the AI Lead; capturing visionary "loud thinking," converting abstract ideas into actionable blueprints, and building production-grade solutions.

You will bridge the gap between technical execution and business strategy: evaluating incoming AI requests, establishing secure experimentation guardrails on Azure and Databricks, and delivering scalable AI applications across GenAI, Agentic AI, and classical ML.

Key Responsibilities

• Strategic Execution & Blueprinting:
• Partner closely with the AI Lead to synthesize strategic goals into clear technical architectures, roadmaps, and execution plans.
• Define end-to-end AI project lifecycles from proof-of-concept (PoC) to full production deployment.
• Use Case Triage & Business Consultation:
• Evaluate business requests from the manufacturing user community; filter hype from high-value, credible AI use cases.
• Guide business stakeholders on AI feasibility, ROI, risk, and expected outcomes with confidence and clarity.
• Hands-on Development & Deployment:
• Design, build, test, and deploy robust AI solutions spanning Generative AI, Agentic workflows, and traditional machine learning models.
• Integrate solutions seamlessly within Microsoft Azure and Databricks ecosystems.
• Provision and manage the required Azure/Databricks cloud infrastructure to enable safe sandbox experimentation for users.