Agentic AI Technical Senior Consultant

Who we are looking for

We are seeking an experienced professional for the Agentic AI Technical Senior Consultant role. The ideal candidate will possess a strong technical background and a proven track record in software engineering and AI implementation.

• Bachelor’s or Master’s degree in Computer Science, Engineering, Information Systems, or a related technical field
• At least 3 years of hands-on experience in software engineering, integration, data engineering, or AI/ML implementation
• Proficiency in Python
• Experience working with APIs (REST, GraphQL), data flows, and system integrations
• Familiarity with cloud platforms (Azure, AWS, or GCP) and related services
• Understanding of version control (Git) and collaborative development practices
• Ability to read and understand solution architecture diagrams and technical designs
• Strong problem-solving skills and willingness to work across both application and integration layers

Preferred Qualifications

• Experience implementing solutions using generative AI, LLMs, or agentic AI platforms
• Familiarity with AI orchestration frameworks/platforms
• Experience with RAG, vector databases, and document ingestion pipelines
• Experience in data engineering and modern data stacks, e.g.: ETL/ELT tools and orchestration (dbt, Apache Airflow, Azure Data Factory, AWS Glue), Data processing (Apache Spark, Databricks, Kafka, Flink), Cloud data warehouses and lakes (Snowflake, BigQuery, Redshift, Azure Synapse, Delta Lake)
• Exposure to enterprise platforms (ServiceNow, Salesforce, SAP, procurement systems, or similar)
• Experience with containerization and deployment (Docker, Kubernetes, CI/CD pipelines)
• Practical experience in consulting or client-facing project delivery

Your future role as Agentic AI Technical Senior Consultant

As an Agentic AI Technical Senior Consultant, you will design, build, and implement AI agent solutions that integrate with complex enterprise environments. At the Senior Consultant level, you will additionally own solution components end-to-end, make key technical design decisions, lead technical workstreams, and guide junior engineers and consultants.

AI Solution Design & Implementation

• Design and implement AI agent workflows, including tool-calling, routing, and orchestration between models, services, and data sources
• Develop and configure backend components (e.g., Python services, APIs, microservices) to support AI agent capabilities
• Integrate AI solutions with enterprise systems (e.g., CRM, ERP, ticketing, knowledge bases, workflow engines)
• Implement retrieval-augmented generation (RAG), prompt orchestration, and guardrails to ensure safe and reliable AI behavior
• Collaborate with architects and business teams to translate solution designs and requirements into technical implementation plans

Platforms, Data & Integration

• Configure and extend AI, automation, and workflow orchestration solutions
• Build and maintain integrations with external APIs, databases, event buses, and message queues
• Implement data pipelines and transformations required for AI use cases (e.g., document ingestion, embedding pipelines, vector stores)
• Ensure that solutions follow client security, privacy, and compliance standards

Quality, Reliability & Operations

• Develop, test, and optimize prompts, workflows, and agent behaviors based on evaluation metrics and user feedback
• Implement monitoring, logging, and basic observability for AI workloads and integrations
• Contribute to non-functional requirements such as robustness, performance, scalability, and resilience of AI solutions
• Participate in code reviews, technical documentation, and handover to client or support teams

Collaboration & Delivery

• Work in cross-functional teams with business analysts, product owners, solution architects, and client IT teams
• Contribute to effort estimation, technical risk identification, and mitigation planning
• Support environment setup, deployment pipelines, and basic DevOps/MLOps practices (in collaboration with platform teams)

Leadership & Ownership

• Lead technical workstreams or solution components on client engagements
• Own key design decisions for AI workflows, integrations, and platform configuration
• Mentor and coach junior team members (technical consultants, analysts)
• Proactively identify architecture, performance, and security risks and drive resolution
• Contribute to practice development, internal accelerators, reusable components, and technical thought leadership in agentic AI

What Deloitte offers

Work on global, high-impact engagements with Fortune 500 clients, building production-grade AI solutions with real business impact. Accelerate your career toward AI architecture, product ownership, or AI strategy, collaborating with colleagues from top consulting firms, including MBB.

About Deloitte

At Deloitte, we support leading global organizations in optimizing and transforming their organizations, including their finance function. Our consultants offer insights, capabilities, and solutions that change the way these organizations operate and make people-related decisions. We are currently building in Poland a dedicated team focusing on advisory in Finance & Performance, advising clients on complex issues relating to Reporting, Budgeting, Controlling processes, and applying the newest technologies.

About the team

Join Deloitte’s rapidly growing Agentic AI practice, where we design and implement next-generation AI agent solutions for global organizations, including Fortune 500, international innovators, and industry leaders. Our teams operate at the intersection of business, technology, and cutting-edge AI, redefining how companies work, automate, and make decisions. If you want to work on high-impact international projects, collaborate with top experts across Deloitte’s global network, and help build solutions that move AI from concept to real-world transformation – this role is for you.

Key skills/competency

• Python
• Generative AI
• LLMs
• AI Orchestration
• Retrieval-Augmented Generation (RAG)
• Cloud Platforms (Azure, AWS, GCP)
• Data Engineering
• System Integration
• Technical Leadership
• Problem-Solving