Deloitte
Consulting · Consulting + audit
Deloitte currently has 140 active AI-related job listings. The majority of these roles, 76%, are focused on the agents stage. The top function for hiring is Engineering, with 135 listings. Frequent tech tags include agent orchestration, model serving, and LLM observability, suggesting a focus on deploying and managing AI systems. In the last 30 days, Deloitte posted 57 new AI roles.
Currently tracking 97 active AI roles, down 97% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $73k–$293k (avg $165k).
Consulting · Consulting + audit
Deloitte currently has 137 active AI-related roles in our index. The most common open titles are: Finance Analytics & AI Manager (4), Finance Analytics & AI Senior Consultant (4), Agentic Software Engineer III (2), Delivery Senior Consultant, Data Engineering and Gen AI (2), Forward Deployed Engineer- AWS (2). Most positions are in Engineering and Product.
Deloitte's active AI hiring is concentrated in: agents (64%), application (15%), serving infrastructure (12%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Job postings at Deloitte most frequently mention: LLM Evaluation & Grading, GCP, AWS, Azure, Model Monitoring.
In the past 30 days, Deloitte has posted 43 new AI-related roles. That is a -73% change versus the prior 30 days (157 → 43).
| Title | Stage | AI score |
|---|---|---|
| AI Data Engineer - Manager AI Data Engineer - Manager role focused on leading data architecture and engineering for AI/ML/GenAI solutions. Designs and operationalizes data foundations for LLM-powered applications, including RAG and vector search. Manages delivery teams, partners with stakeholders, and ensures data governance, quality, and monitoring. Blends technical leadership with delivery management and team development, driving engineering standards and outcomes in client environments. Contributes to AI/ML/GenAI technical direction, architectural design, technology selection, and MLOps/LLMOps. Conducts research for scalable AI solutions, leads development of AI models, and collaborates with various teams. Serves as a technical advisor, ensures operational excellence, and addresses risks and ethical considerations in AI implementation. | DataAgent | 7 |
| Kinaxis Senior Consultant This role involves implementing and optimizing supply chain planning solutions using Kinaxis Maestro, leveraging advanced analytics, AI, and ML. The consultant will lead solution design, configuration, integration, and team management, focusing on data analytics and mathematical modeling techniques within the supply chain domain. |
| Data |
| 5 |
| ConvergeHEALTH - Data Operations Engineer, Expert Services-Innovation_Delivery_Transformation Data Operations Engineer on Converge for Healthcare's Expert Services team, responsible for designing and operating cloud-native data pipelines that turn healthcare data into decision-ready analytics. This role involves data integration, validation, profiling, quality assurance, and enabling analytics through BI dashboards and ML Lab workflows. The engineer will also focus on automation, orchestration, and collaborating on product evolution, using emerging AI tooling and LLM-enabled data exploration. | Data | 5 |
| Manager - Data Science / Data Lake Manager role focused on designing and modernizing cyber data, analytics, and security operations capabilities for clients, applying AI/ML and data engineering to cybersecurity use cases like detection engineering and threat hunting. Requires experience with cyber data platforms, cloud technologies, and AI development tools. | Data | 5 |
| Data Foundations Engineer Designs and scales modern data architectures powering Wallet, Payments, and Commerce products. Focuses on building high-performance data pipelines and enabling analytics and ML use cases, with strong fundamentals in data modeling and scalable systems. Requires experience with data engineering for analytics or ML systems, SQL, Python/Scala/Java, Spark, Kafka, Airflow, data modeling, lakehouse architectures, cloud platforms (AWS/Azure/GCP), Snowflake/Databricks, CI/CD, data observability, MLOps, GenAI/RAG pipelines, and LLMs. Experience in FinTech, Wallet, or Payments domain is required. | DataAgent | 5 |
| Consultant - Data Science / Data Lake This role involves applying AI, ML, and data engineering methods to cybersecurity use cases like detection engineering and threat hunting. It focuses on modernizing cyber data environments and improving data operations for clients. The role requires experience with AI development tools (e.g., vector databases, LangChain), data preparation, feature engineering, and visualization using languages like Python, SQL, R, or SAS, within a client-facing consulting context. | Data | 5 |
| Delivery Consultant, Data Engineering and Gen AI Consultant role focused on designing, building, and maintaining data pipelines and integration workflows for government clients, with a focus on supporting AI and Gen AI use cases. Requires experience in data engineering, Python, SQL, and cloud platforms. | Data | 5 |