Deloitte
AI Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an AI Engineer with a likely 6-month contract in Glasgow, paying an inside IR35 rate. Key skills include Google ADK, LLM, ML, API integration, and experience in banking-related AI use cases.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
August 19, 2026
🕒 - Duration
More than 6 months
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🏝️ - Location
Hybrid
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📄 - Contract
Inside IR35
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🔒 - Security
Unknown
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📍 - Location detailed
Glasgow, Scotland, United Kingdom
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🧠 - Skills detailed
#Cloud #Observability #AI (Artificial Intelligence) #Scala #Classification #Deployment #Data Engineering #Monitoring #Databases #Compliance #ML (Machine Learning) #API (Application Programming Interface)
Role description
Contract Job Title: AI Engineer (Google ADK, LLM, ML, A2A)
Contract Start Date: TBC
Contract Length: Likely 6 months
Contract Classification: Inside IR35
Contract Location: Glasgow (2/3 days in the office)
· Design, build, and deploy AI agents using Google’s Agent Development Kit (ADK) and Vertex AI Agent Builder, integrating with APIs and systems.
· Develop and orchestrate Agent-to-Agent (A2A) communication flows, enabling collaboration, task delegation, and information sharing among agents.
· Implement LLM-based components, prompt templates, function calling, structured outputs using frameworks.
· Build and optimize RAG pipelines integrating Vertex AI Search / Matching Engine, vector databases and document stores.
· Engineer context and memory modules for agents, defining knowledge retrieval, embedding strategies, and session continuity logic.
· Develop API integrations and connectors enabling real-time data exchange between agents, backend services, and UI/UX interfaces.
· Collaborate with data and ML teams to design ML workflows preprocessing, fine-tuning, deployment, and monitoring on Vertex AI Pipelines.
· Apply prompt engineering and grounding techniques to ensure model responses are contextually accurate, explainable, and compliant.
· Ensure scalability, observability, and compliance of deployed agents across hybrid (cloud + on-prem) infrastructures.
· Partner with Data Engineers, UI/UX teams, AI Architects and Product teams to translate business requirements into technical agent logic, testing strategies, and continuous improvement loops.
· Experience with handling quantitative / numerically heavy use cases
· Experience with banking related AI/GenAI use cases
Contract Job Title: AI Engineer (Google ADK, LLM, ML, A2A)
Contract Start Date: TBC
Contract Length: Likely 6 months
Contract Classification: Inside IR35
Contract Location: Glasgow (2/3 days in the office)
· Design, build, and deploy AI agents using Google’s Agent Development Kit (ADK) and Vertex AI Agent Builder, integrating with APIs and systems.
· Develop and orchestrate Agent-to-Agent (A2A) communication flows, enabling collaboration, task delegation, and information sharing among agents.
· Implement LLM-based components, prompt templates, function calling, structured outputs using frameworks.
· Build and optimize RAG pipelines integrating Vertex AI Search / Matching Engine, vector databases and document stores.
· Engineer context and memory modules for agents, defining knowledge retrieval, embedding strategies, and session continuity logic.
· Develop API integrations and connectors enabling real-time data exchange between agents, backend services, and UI/UX interfaces.
· Collaborate with data and ML teams to design ML workflows preprocessing, fine-tuning, deployment, and monitoring on Vertex AI Pipelines.
· Apply prompt engineering and grounding techniques to ensure model responses are contextually accurate, explainable, and compliant.
· Ensure scalability, observability, and compliance of deployed agents across hybrid (cloud + on-prem) infrastructures.
· Partner with Data Engineers, UI/UX teams, AI Architects and Product teams to translate business requirements into technical agent logic, testing strategies, and continuous improvement loops.
· Experience with handling quantitative / numerically heavy use cases
· Experience with banking related AI/GenAI use cases
