AI Architect

TestYantra Software Solutions; Böblingen; Vor Ort; EUR 90.000 - 130.000; Vollzeit

Benefits dieser Stelle

Health insurance

Zusammenfassung

TestYantra Software Solutions in Germany is seeking a Lead AI Solutions Engineer to drive strategic AI initiatives for a global manufacturing client. You will translate vision into production-grade blueprints and bridge technical execution with business goals.

You will lead end-to-end AI projects across GenAI, Agentic AI, and classical ML; manage Azure and Databricks deployments, guardrails, governance, and collaboration with IT and operations teams.

Qualifikationen

• Proven track record delivering AI/ML at scale.
• Experience with GenAI, Agentic workflows and LLMs.
• Strong ability to translate vision into architecture and roadmaps.
• Effective communication with non-technical stakeholders.

Aufgaben

• Strategic execution: synthesize goals into architectures, roadmaps, and plans.
• Evaluate AI requests and define credible, high-value use cases.
• Hands-on development: design, build, test, and deploy AI solutions.
• Guardrails: governance, security, Responsible AI, and telemetry.
• Stakeholder collaboration across IT, Data Eng, Security, and Ops.

Kenntnisse

GenAI

AI/ML

Consultative mindset

Communication

Azure

Databricks

Docker/Kubernetes

Tools

Azure OpenAI Service

Azure ML

Databricks

Docker

Kubernetes

Jobbeschreibung

Job Summary:

We are seeking a technical and consultative Lead AI Solutions Engineer 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.
• Infrastructure, Guardrails & Experimentation:
• Provision and manage the required Azure/Databricks cloud infrastructure to enable safe sandbox experimentation for users.
• Implement governance, security protocols, Responsible AI guardrails, cost-tracking, and telemetry across all AI deployments.
• Stakeholder Management:
• Communicate complex technical concepts effectively to non-technical business leaders and operational teams.
• Drive alignment across cross-functional enterprise teams, including IT, Data Engineering, Security, and Business Operations.

Technical Expertise

• AI & GenAI: Deep understanding of Machine Learning fundamentals, Deep Learning, Large Language Models (LLMs), Fine-Tuning, RAG (Retrieval-Augmented Generation), and Agentic Frameworks (e.g., LangChain, AutoGen, CrewAI, Semantic Kernel).
• Cloud Platform: Advanced hands‑on experience with Microsoft Azure (Azure OpenAI Service, Azure ML, Azure Functions, Azure Cosmos DB/Vector Stores).
• Data Engineering: Strong proficiency in Databricks (PySpark, Delta Lake, MLflow, Unity Catalog) for data processing and model deployment.
• DevOps/MLOps: Experience setting up CI/CD pipelines, containerization (Docker, Kubernetes), and monitoring for AI workloads.

Core Competencies

• Consultative & Analytical Mindset: Strong capability to dissect hype, assess technical feasibility, and prioritize business impact.
• Communication: Exceptional verbal and written communication skills to manage stakeholders, lead technical reviews, and articulate complex solutions clearly.

Preferred Experience

• Proven track record of working on Microsoft Azure and Databricks platforms.
• 5+ years of experience in Data Science, Machine Learning, or AI Engineering.
• 2+ years of hands‑on experience designing and deploying GenAI/Agentic solutions in enterprise environments.