Agentic & Generative AI Consultant
Role details
Job location
Tech stack
Job description
Generative AI Leader . This is a senior, high-impact role for a visionary who can operate both as a trusted advisor to executive stakeholders and as a hands-on technical leader driving delivery of enterprise-grade AI solutions.The Opportunity
You will define and lead the organisations Generative AI strategy, translating cutting-edge capabilities into real business value. The role requires a rare blend of commercial advisory expertise, architectural oversight, and technical delivery leadership across large-scale AI programmes.Key Responsibilities
Define and execute the enterprise Generative AI strategy aligned to business objectives
Advise C-suite and senior stakeholders on AI adoption, governance, risk, and value realisation
Lead the design, architecture, and delivery of GenAI solutions from concept to production
Establish AI operating models, best practices, and responsible AI frameworks
Build and lead high-performing multidisciplinary teams (Data Science, ML Engineering, MLOps)
Identify use cases across functions (customer experience, operations, knowledge management, automation)
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Requirements
Proven leadership delivering Generative AI programmes at enterprise scale
Strong advisory background engaging senior business leaders
Deep technical expertise across modern AI/ML ecosystems
Track record of translating emerging technologies into measurable outcomes
Technical Expertise
Generative AI & LLMsLarge Language Models (GPT, Claude, Llama, Mistral or similar)
Prompt engineering, fine-tuning, RAG (Retrieval Augmented Generation)
Multimodal AI (text, image, audio, video)
Agentic frameworks and orchestration
AI/ML EngineeringPython, PyTorch, TensorFlow, JAX
NLP, deep learning, model optimisation
Evaluation frameworks and guardrails
Data & PlatformsVector databases (Pinecone, Weaviate, FAISS, Milvus)
Knowledge graphs and semantic search
Data engineering pipelines
MLOps & DeploymentCI/CD for ML, model monitoring, versioning
Kubernetes, Docker, serverless architectures
MLflow, Kubeflow, SageMaker or similar
Cloud & ArchitectureAzure AI, AWS AI/Bedrock, Google Vertex AI
API-led architectures and microservices
Security, governance, and responsible AI
Frameworks & ToolingLangChain, LlamaIndex, Semantic Kernel or equivalent
Integration with enterprise systems (CRM, ERP, collaboration platforms)
Desirable
Experience in regulated environments
AI ethics, governance, and compliance knowledge
Background in consulting or digital transformation