Description & Requirements
It would be an advantage if you also have:
• Experience with AI orchestration frameworks or platforms
• Experience with RAG, vector databases, prompt orchestration, guardrails, and document ingestion pipelines
• Experience with data engineering tools and modern data stacks, such as dbt, Apache Airflow, Azure Data Factory, AWS Glue, Apache Spark, Databricks, Kafka, Flink, Snowflake, BigQuery, Redshift, Azure Synapse, or Delta Lake
• Exposure to enterprise platforms such as ServiceNow, Salesforce, SAP, procurement systems, workflow engines, or similar
• Experience with containerization and deployment tools such as Docker, Kubernetes, and CI/CD pipelines
• Experience with Infrastructure as Code, especially Terraform
• TypeScript development experience, especially for service integrations, tooling, or frontend/backend components
• Practical experience in consulting or client-facing project delivery
• Experience defining business requirements, use cases, user stories, or functional specifications
• Experience leading technical workstreams or mentoring junior team members
As an Agentic AI Technical Senior Consultant, you will design, build, and implement AI agent solutions that integrate with complex enterprise environments. You will work closely with clients and Deloitte teams to understand business requirements, validate use cases, make technical design decisions, and deliver practical AI solutions.
In this role, you will:
• Design and implement AI agent workflows, including tool-calling, routing, and orchestration between models, services, and data sources
• Develop and configure backend components, such as Python services, APIs, microservices, and integration layers
• Integrate AI solutions with enterprise systems, including CRM, ERP, ticketing platforms, knowledge bases, and workflow engines
• Implement RAG, prompt orchestration, guardrails, and evaluation mechanisms to support safe and reliable AI behavior
• Build data layers that support agentic solutions with structured and unstructured data, including ingestion, transformation, retrieval, and governance considerations
• Translate business requirements and solution designs into technical implementation plans
• Lead technical workstreams or own specific solution components on client engagements
• Make technical design decisions related to AI workflows, integrations, platform configuration, and solution quality
• 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
• Participate in code reviews, technical documentation, deployment activities, and handover to client or support teams
• Identify technical, architectural, performance, or security risks and support their resolution
• Mentor junior consultants and engineers, supporting their technical growth and delivery quality
• Contribute to internal accelerators, reusable components, and practice development in the area of agentic AI
• Exposure to enterprise-grade AI solutions, modern technology stacks, and complex client environments
• A role with strong technical ownership and the opportunity to lead solution components or workstreams
• Collaboration with experienced colleagues across consulting, technology, architecture, data, and AI
• Opportunity to grow toward AI architecture, technical leadership, product ownership, or AI strategy roles
• A learning-oriented environment where you can develop both advanced technical and consulting skills
• Technical interview focused on your engineering, integration, cloud, AI implementation, and solution design experience
• Business or case discussion with the hiring team to understand your approach to client scenarios, technical ownership, and delivery leadership
• Final conversation and offer discussion
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