Deloitte
Consulting · Consulting + audit
Currently tracking 97 active AI roles, down 97% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $73k–$293k (avg $165k).
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.
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 responsible for leading data architecture and engineering for AI/ML/GenAI solutions, including RAG, embeddings, and vector search. The role involves managing a team, translating use cases into production pipelines, and ensuring data governance, quality, and monitoring. It also includes defining technical direction, designing end-to-end AI architectures, selecting technologies, and contributing to MLOps/LLMOps. | DataAgent | 7 |
| Data Analytics Senior Consultant - Data Lake This role focuses on building and modernizing cyber data and analytics programs, leveraging AI and ML for cyber defense and operations. It involves working with cyber security cloud platforms, data platforms, and AI development tools like vector databases and frameworks. The role requires experience in statistical analysis, machine learning, data mining, and preparing data for analysis using languages like Python and SQL, with a focus on cyber specific use cases. | DataAgent | 7 |
| 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 |
| AI/ML Engineer (TS/SCI Poly) AI/ML Engineer role focused on developing and maintaining data pipelines, applying machine learning techniques, and building/optimizing AI/ML solutions for client missions, requiring a TS/SCI Polygraph clearance. | Data | 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 |
| Google Data Engineering Consultant This role focuses on building and supporting cloud-based data and AI solutions on Google Cloud Platform (GCP). The Data Engineer II will design, develop, test, and deploy data pipelines, platform components, and AI-enabled solutions, with a focus on data preparation, feature engineering, model testing, and model evaluation. | DataServe | 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 |
| QRM - Quality Analytics and Enablement Manager - C_MAT This role focuses on leveraging data science, predictive modeling, and AI tools to identify, quantify, and manage delivery risks within client engagements. The manager will design and enhance analytic tools and dashboards, integrate advanced analytics capabilities, and analyze multi-source risk data to provide actionable insights for Quality and Risk Leadership. The role requires experience in machine learning, data wrangling, and data visualization, with a strong emphasis on translating model outputs into business decisions and stakeholder engagement. | 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 |
| Financial Modeling & Data Analytics Manager Manager role focused on financial modeling and data analytics, integrating financial models with enterprise data and technology solutions, and applying AI capabilities in financial modeling and advisory work. The role involves developing and delivering financial models, generating data-driven insights, and advising clients on strategic decisions. | Data | 5 |
| Workforce Data & Analytics Manager Manager for Deloitte's Workforce Data & Analytics Team, focusing on leveraging data, data science, analytics, visualization, platforms, and AI to uncover insights and inform decision-making within the people domain. The role involves leading client engagements on people data and analytics strategy, designing data pipelines, and developing analytics solutions including predictive models. | Data | 5 |
| Delivery Senior Consultant, Data Engineering and Gen AI This role focuses on data engineering and conversion solutions, specifically for government clients, with an emphasis on "Gen AI". The core responsibilities involve designing, building, and supporting data pipelines, integration workflows, and performing data mapping, transformation, migration, and validation. While it mentions "Gen AI" and "AI & Data team", the primary focus is on the underlying data infrastructure and engineering, rather than direct AI model development or research. The role is classified as AI-related because it supports AI initiatives through robust data engineering, but the direct AI contribution is more adjacent. | Data | 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 |
| ConvergeHEALTH - Data Operations Engineer, Expert Services-Innovation_Delivery_Transformation Data Operations Engineer for ConvergeHEALTH's Expert Services team, responsible for building and operating cloud-native data pipelines that integrate client healthcare data into Deloitte's Data Studio platform. This role involves data engineering, cloud operations, and applying AI tooling for analytics and anomaly detection, with a focus on creating reliable, decision-ready analytics from complex healthcare data. | Data | 5 |
| Lead Data Expert Lead Data Expert for Deloitte's AI & Engineering team, focusing on Personnel & Readiness enterprise analytics. This role involves technical leadership in designing and implementing advanced analytics solutions, consultative solutioning, algorithmic innovation (forecasting models), data visualization, and stakeholder engagement. The position requires guiding teams in data wrangling, architecture, automation, and validation, with a focus on federal compliance standards and project lifecycle management. Experience with agentic infrastructure is also mentioned. | Data | 5 |
| Data Foundations Engineer Data Foundations Engineer responsible for designing and scaling modern data architectures, building high-performance data pipelines, and enabling analytics and ML use cases. Focuses on data modeling and scalable systems within the Wallet, Payments, and Commerce products, with exposure to MLOps, GenAI/RAG, and LLMs. | Data | 5 |
| Data Foundations Engineer Data Foundations Engineer responsible for designing and scaling modern data architectures, building high-performance data pipelines, and enabling analytics and ML use cases. The role requires strong fundamentals in data modeling, scalable systems, and experience with cloud platforms and data processing tools. Exposure to MLOps, GenAI/RAG pipelines, and LLMs is also required, with a focus on the FinTech, Wallet, or Payments domain. | DataAgent | 5 |
| Kinaxis Solution Architect Manager Manager responsible for overseeing end-to-end solution delivery for Kinaxis supply chain planning implementations, involving process design, data analytics, system configuration, and deployment. Requires expertise in optimization methods, statistical analysis, advanced mathematical modeling, and exposure to data science and advanced planning systems. | Data | 5 |
| Data Scientist (TS/SCI Poly) Develops, implements, and maintains data pipelines and applies advanced data science techniques, including machine learning, spatial analysis, and time-series modeling, to extract insights for mission-critical operations. Builds, tests, and optimizes AI/ML solutions for integration into user-facing tools. Requires TS/SCI Polygraph clearance and 3+ years of experience in data engineering/analytics and 2+ years with Python and SQL. | Data | 5 |