Agentic AI Technical Consultant | Poland

Deloitte's growing Agentic AI practice focused on designing and delivering next-generation AI agent solutions for enterprise clients. The team combines business, technology, and applied AI expertise to create scalable, reliable solutions for complex enterprise environments. Collaboration involves local and international Deloitte teams, working on client engagements to produce production-ready AI solutions.

• Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or related technical field.
• At least 1 year of hands-on experience in software engineering, integration, data engineering, or AI/ML implementation.
• Practical experience with generative AI or agentic AI solutions, including AI workflow implementation or configuration.
• Strong Python skills and experience working with APIs, data flows, and system integrations.
• Familiarity with cloud platforms such as Azure, AWS, or GCP.
• Understanding of Git, collaborative development practices, and technical documentation.
• Strong problem-solving skills and willingness to work across application, integration, and data layers.
• EU work permit.

Nice to have:

• Experience with RAG, vector databases, document ingestion pipelines, or AI orchestration frameworks.
• Exposure to enterprise platforms such as ServiceNow, Salesforce, SAP, procurement systems, or similar.
• Experience with data engineering tools and modern data stacks such as dbt, Airflow, Azure Data Factory, Spark, Databricks, Kafka, Snowflake, BigQuery, Redshift, Azure Synapse, or Delta Lake.
• Experience with Docker, Kubernetes, CI/CD pipelines, Terraform, or other DevOps/MLOps practices.
• TypeScript development experience for integrations, tooling, or frontend/backend components.
• Previous consulting experience, client-facing delivery, or defining business requirements, use cases, user stories, or functional specifications.

• Design and implement AI agent workflows, including tool-calling, routing, orchestration, and integration between models, services, and data sources.
• Build and configure backend components such as Python services, APIs, and microservices to support AI agent capabilities.
• Integrate AI solutions with enterprise systems, including CRM, ERP, ticketing tools, knowledge bases, and workflow engines.
• Implement RAG, prompt orchestration, guardrails, and evaluation mechanisms to support safe and reliable AI behavior.
• Build data layers for agentic solutions, covering ingestion, transformation, retrieval, and governance considerations.
• Work with architects, business teams, and client stakeholders to translate requirements into technical implementation plans.
• Support testing, monitoring, logging, documentation, handover, and continuous improvement of AI workloads.

EU work permit required.