AI Consultant (m/f/d)

EPAM Systems; Deutschland; Hybrid; EUR 90.000 - 120.000; Vollzeit

Zusammenfassung

EPAM Systems in Germany is seeking an AI Consultant (m/f/d) to join our Data & AI Practice in a hybrid mode. You will prototype and deliver AI-driven solutions for enterprise clients using GenAI and agentic systems, translating business needs into measurable demos.

You will work with stakeholders to design use cases, ensure regulatory compliance, and leverage platforms like Databricks, Snowflake and MS Foundry to showcase tangible impact.

Qualifikationen

• Applied data science with modern AI techniques.
• Domain experience in Manufacturing, Life Sciences, Logistics, Automotive or Energy.
• Knowledge of statistical methods and ML fundamentals.
• Ability to rapidly prototype AI solutions using current AI platforms and frameworks.
• Familiarity with AI platforms and model management tools.
• Awareness of AI/ML risks, constraints and regulations (EU AI Act, GDPR).
• Fluency in German and English with client-facing workshops.
• Strong communication and presentation skills for business and technical audiences.
• Experience managing client relationships in dynamic delivery environments.
• Demonstrated engagement with AI through projects, research or experiments.
• Specialist knowledge in ML techniques, AI regulation, security, or deep learning.

Aufgaben

• Partner with business and IT stakeholders to identify AI value opportunities.
• Prototype AI solutions using modern AI platforms with iterative client engagement.
• Translate business problems into AI use cases, defining objectives and required data sources.
• Design Generative AI and agentic solutions, including RAG patterns, from prototype to client-ready demos.
• Orchestrate AI agents using platforms like Databricks Agent Framework, Snowflake Cortex or Microsoft Foundry.
• Contribute to AI and agentic solution architectures with Solution Architects and Technical Leads.
• Apply domain knowledge from core industries to contextualize solutions.
• Present AI solutions and outcomes using visual storytelling for technical and business audiences.
• Develop and justify business cases for AI adoption focusing on cost-benefit and risk.
• Identify risks, limitations and compliance issues (EU AI Act, GDPR) throughout design and delivery.

Kenntnisse

Modern AI tech

Domain experience

Statistics & ML basics

Rapid prototyping

AI platforms familiarity

AI risk awareness

German & English fluency

Client communication

Stakeholder management

Hands-on AI projects

Specialist ML/AI knowledge

Tools

Databricks

Snowflake

Microsoft Foundry

AWS

GCP

Jobbeschreibung

We're looking for an AI Consultant (m/f/d) to join our Data & AI Practice team in Germany in a hybrid working mode. In this role, you will act as a rapid innovator, using hands-on expertise in modern AI, Generative AI and agentic systems to prototype and deliver AI-driven solutions for enterprise clients. Leveraging a strong applied data science background, you will quickly interpret business needs, design practical use cases and transform ideas into working demonstrations that showcase measurable impact. If you are passionate about bridging business challenges with AI-enabled solutions and influencing real-world adoption, this opportunity allows you to shape how organizations integrate and scale next-generation AI technologies.

Responsibilities

• Partner with business and IT stakeholders to identify opportunities where AI delivers measurable value
• Rapidly prototype AI solutions using modern AI platforms, tools and frameworks with iterative client engagement
• Translate business problems into AI use cases, defining objectives, success criteria and required data sources
• Design and build Generative AI and agentic solutions, including RAG patterns, from prototype to client-ready demonstration
• Orchestrate AI agents using platforms such as Databricks Agent Framework, Snowflake Cortex or Microsoft Foundry
• Contribute to AI and agentic solution architectures in collaboration with Solution Architects and Technical Leads
• Apply domain knowledge from at least one core industry (Manufacturing, Life Sciences, Logistics, Automotive or Energy) to contextualize solutions
• Present AI solutions and outcomes using visual storytelling for technical and business audiences
• Develop and justify business cases for AI adoption, focused on cost-benefit and risk analysis
• Identify risks, limitations and compliance issues (e.g., EU AI Act, GDPR) throughout solution design and delivery

Requirements

• Practical expertise with modern AI technologies (including GenAI and agentic systems) gained from applied data science roles
• Domain experience in at least one industry: Manufacturing, Life Sciences, Logistics, Automotive or Energy
• Knowledge of statistical methods, predictive modeling and machine learning fundamentals
• Ability to rapidly prototype AI solutions using current AI platforms, tools and frameworks
• Familiarity with AI platforms (Databricks, Snowflake, Microsoft Foundry, AWS or GCP) and supporting tools for model management
• Awareness of AI/ML risks, constraints and emerging regulations (EU AI Act, GDPR)
• Fluency in German and English, with proven experience in client-facing workshops and discussions
• Strong communication and presentation skills adaptable to business and technical stakeholders
• Confidence managing client relationships in dynamic, ambiguous delivery environments
• Demonstrated personal engagement with AI through projects, research or experimentation
• Specialist knowledge in at least one area: ML techniques, AI regulation, security, agentic systems or deep learning

Nice to have

• Professional certification in major AI/data platforms (Azure, Databricks, AWS, GCP)
• Experience engineering or scaling large AI/ML systems in production settings
• Familiarity with AI/ML monitoring, observability and MLOps/AIOps patterns
• Exposure to AI-assisted development tools or frameworks
• Ability to prepare and present RFP responses and solution proposals
• Experience in business process mapping for agentic AI workflows
• Knowledge of vector database technologies for RAG architectures