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In office (Warsaw)
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Employment
Full-Time

First seen by Alion on Nov 10, 2026. Deloitte scores A on the Alion truth index.

Overview
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Deloitte is one of the "Big Four" global accounting and professional services firms, providing audit, tax, consulting, and risk advisory services to organizations worldwide. Founded in London in 1845, it operates as a multinational network of independent member firms spanning over 150 countries and territories. Known for its extensive market reach and industry expertise, the organization serves a vast majority of the Fortune Global 500 companies.


Join Deloitte's growing Agentic AI practice and help shape the next generation of enterprise AI solutions.
We work with organizations across industries to design and implement AI agent solutions that automate processes, improve decision-making, and support real business outcomes in complex enterprise environments. In this role, you will collaborate with local and international Deloitte teams, work on client engagements, and help turn AI concepts into production-ready solutions.

About the team:

You will join a growing Agentic AI practice focused on designing and delivering next-generation AI agent solutions for enterprise clients. The team works at the intersection of business, technology, and applied AI, combining technical delivery with consulting expertise to create solutions that are scalable, reliable, and ready for real-world use.

What we offer:
  • Opportunity to work on international AI engagements with real business impact.
  • Exposure to enterprise-grade AI solutions, modern technology stacks, and complex client environments.
  • Collaboration with experienced colleagues across consulting, technology, architecture, data, and AI.
  • A clear path to grow toward AI architecture, technical leadership, product ownership, or AI strategy roles.
  • A learning-oriented environment where you can develop both technical and consulting skills.

Zakres obowiązków

  • 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.

Wymagania

  • Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or a 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 implementation or configuration of AI workflows.
  • 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 experience in consulting, client-facing delivery, or defining business requirements, use cases, user stories, or functional specifications.

Tech stack

  • AI
  • Degree
  • Data engineering
  • Python
  • System integration
  • Cloud
  • Azure
  • AWS
  • GCP
  • Git
  • Salesforce
  • SAP
  • dbt
  • Airflow
  • Spark
  • Databricks
  • Kafka
  • Snowflake
  • BigQuery
  • Redshift
  • Azure Synapse
  • Docker
  • Kubernetes
  • CD pipelines
  • Terraform
  • DevOps
  • MLOps
  • TypeScript
  • Defining business requirements
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