Find the expertise your AI project needs.
From the first business question to the system people use every day.
Choose the expertise you need and where you are in the project. Then refine by specific skills, relevant experience, and reviewed evidence.
This is the breadth we’re building toward. It is not a claim that every specialty is already available.
Strategy, architecture & adoption
| Area of expertise | Examples of work |
|---|---|
| AI Strategy & Business Transformation | Use-case discovery, readiness assessments, business cases, roadmaps, operating models, and adoption planning. |
| Enterprise & AI Solution Architecture | End-to-end solution design, technology selection, build-versus-buy decisions, integration, and requirements. |
| AI Product & Experience Design | Product discovery, user research, human–AI interaction, conversational experiences, accessibility, and usability evaluation. |
Data, models & intelligent applications
| Area of expertise | Examples of work |
|---|---|
| Data Science & Decision Intelligence | Forecasting, recommendations, experimentation, optimization, anomaly detection, and decision support. |
| Data Engineering & Knowledge Systems | Data pipelines, quality, databases, knowledge graphs, document processing, retrieval, and data preparation. |
| Machine Learning & AI Research | Model development, deep learning, training methods, fine-tuning, research reproduction, and applied experimentation. |
| Generative AI, Language Models & Agents | Retrieval-augmented generation, model adaptation, prompt and context design, agent workflows, and tool integration. |
| Computer Vision, Speech & Multimodal AI | Image and video understanding, speech recognition and generation, document intelligence, and combined-input systems. |
| Robotics, Autonomous Systems & Edge AI | Perception, planning, control, simulation, embedded inference, sensor integration, and edge deployment. |
Software, platforms & infrastructure
| Area of expertise | Examples of work |
|---|---|
| AI Application & Software Engineering | Backend and frontend applications, APIs, integrations, workflow automation, testing, and connections to existing systems. |
| Cloud, Platform Engineering & MLOps | Cloud architecture, deployment pipelines, model serving, orchestration, model lifecycle management, and automation. |
| Compute, Accelerators & HPC | GPUs and accelerators, servers, operating systems, cluster scheduling, parallel computing, and workload optimization. |
| Networking & AI Fabrics | Cluster fabrics, connectivity, routing, network automation, and communication-performance troubleshooting. |
| Storage & Data Protection | Storage architecture, availability, backup, recovery, checkpointing, and training/inference data delivery. |
| Data Center Engineering | Power, cooling, rack integration, physical capacity, commissioning, and facility efficiency. |
Trust, performance & delivery
| Area of expertise | Examples of work |
|---|---|
| Cybersecurity & Privacy Engineering | Threat modeling, identity and access, application and infrastructure security, AI security testing, and privacy controls. |
| Responsible AI & Governance | Risk assessment, governance processes, documentation, human oversight, fairness evaluation, and assurance evidence. |
| AI Evaluation, Performance & Reliability | Model-quality evaluation, benchmarking, load tests, observability, resilience, inference efficiency, and cost/energy analysis. |
| Technical Delivery, Training & Service Management | Program and project delivery, supplier coordination, operational handover, training, and knowledge transfer. |
Other expertise
A specialist discipline, an emerging capability, or a combination that does not fit the list? Tell us what you have in mind.
Where are you in the project?
Discovery & Assessment · Strategy & Planning · Architecture & Design · Proof of Concept & Pilot · Implementation & Integration · Validation & Acceptance · Deployment & Handover · Operations & Support · Optimization & Scaling · Retirement & Decommissioning · Other
Have a particular initiative?
New Implementation · Migration & Consolidation · Upgrade & Modernization · Troubleshooting & Recovery · Assessment & Independent Review · Training & Knowledge Transfer · Other
Choose any that apply. An initiative can span several stages; Other can be selected alongside the existing categories.
Different challenges. One connected network.
| Your challenge | Relevant expertise and stage | What to look for |
|---|---|---|
| Which AI idea should we pursue? | AI Strategy × Discovery & Assessment | Use-case evaluation, readiness, business case, and a practical roadmap. |
| We want an assistant that uses our internal knowledge. | Generative AI + Data Engineering × Architecture & Design | Retrieval, access controls, document preparation, application integration, and evaluation. |
| Our vision model struggles outside the lab. | Computer Vision + Edge AI × Validation & Acceptance | Representative tests, error analysis, robustness, and deployment-context review. |
| We need an agent to complete a business workflow reliably. | AI Agents + Software Engineering × Implementation & Integration | Tool integration, exceptions, test cases, workflow controls, and human approvals. |
| Our forecasts need to improve operational decisions. | Data Science × Proof of Concept & Pilot | Baselines, suitable measures, experimentation, and integration into decisions. |
| We need an independent assessment before deployment. | AI Governance + Security + Evaluation × Validation & Acceptance | Risk review, testing, limitations, and acceptance evidence. |
| Inference costs are growing faster than usage. | Performance Engineering + MLOps × Optimization & Scaling | Workload analysis, serving configuration, and quality-versus-cost comparisons. |
| Training does not scale as expected. | Compute + Networking × Operations & Support | Measurement planning, bottleneck analysis, and targeted troubleshooting. |
Specific skills. Clear context. Relevant evidence.
Illustrative skills: RAG evaluation · Multilingual speech recognition · Recommendation-system experimentation · Agent tool integration · Model quantization · Edge vision optimization · Knowledge-graph design · AI security testing · Distributed-training diagnosis · RoCEv2 congestion troubleshooting
A skill is more useful when you can see what someone worked on, what they actually did, and what evidence supports it.
Not sure which specialist you need?
Describe the outcome, the obstacle, or the next decision. You should not have to know the right job title before asking for help.