

SoftNice
AI Specialist
β - Featured Role | Apply direct with Data Freelance Hub
This role is for an AI Specialist (AI Foundry) in Leeds (Hybrid) on a 3-month contract with an immediate start. Requires 10+ years in Data & AI, expertise in LLMs, agentic AI, and experience in financial services or regulated industries.
π - Country
United Kingdom
π± - Currency
Β£ GBP
-
π° - Day rate
Unknown
-
ποΈ - Date
April 1, 2026
π - Duration
3 to 6 months
-
ποΈ - Location
Hybrid
-
π - Contract
Unknown
-
π - Security
Unknown
-
π - Location detailed
Leeds, England, United Kingdom
-
π§ - Skills detailed
#GCP (Google Cloud Platform) #Data Governance #Data Quality #Scala #AWS (Amazon Web Services) #AI (Artificial Intelligence) #Data Engineering #Databases #"ETL (Extract #Transform #Load)" #Cloud #Strategy #Azure
Role description
Job Title
β’ AI Specialist (AI Foundry)
Location
β’ Leeds (Hybrid β 3 days onsite per week)
Job Type
β’ Contract (3 Months)
Start Date
β’ Immediate
Experience Required
β’ 10+ years in Data & AI / Applied AI Engineering
Key Skills
β’ LLMs
β’ agentic AI
β’ AI system design
β’ RAG architectures
β’ vector databases
β’ cloud platforms: Azure, AWS, or GCP
β’ AI governance, ethics, and regulatory frameworks
β’ multi-agent systems
β’ orchestration frameworks
β’ data engineering
β’ data governance
β’ designing scalable, secure AI solutions
β’ stakeholder management
β’ executive communication skills
β’ mentoring and leading AI capability development
Responsibilities
β’ Define and contribute to AI strategy, roadmap, and governance frameworks
β’ Lead enterprise assurance for high-risk AI systems and conduct deep technical reviews
β’ Act as SME for AI technologies including LLMs and agentic AI
β’ Design and evaluate multi-agent systems (memory, planning, orchestration, autonomy controls)
β’ Lead PoCs for advanced AI workflows and semi-autonomous systems
β’ Define enterprise AI patterns (RAG, vector search, prompt governance, orchestration)
β’ Provide technical advisory on model selection, prompting strategies, and architecture trade-offs
β’ Establish AI standards, guardrails, and reusable frameworks
β’ Drive AI enablement through tooling, accelerators, and evaluation frameworks
β’ Mentor teams and uplift AI capability across the organization
β’ Ensure strong data foundations (data quality, lineage, governance, privacy)
β’ Challenge vendor solutions through benchmarking and risk assessment
Qualifications
β’ Experience in financial services or regulated industries
β’ Exposure to enterprise-scale transformation programs
β’ Strong commercial awareness and business case support
β’ Strong communication and stakeholder influence
β’ Strategic thinking with execution focus
β’ Ability to operate in ambiguous, fast-paced environments
β’ Problem-solving mindset with high ownership
Job Title
β’ AI Specialist (AI Foundry)
Location
β’ Leeds (Hybrid β 3 days onsite per week)
Job Type
β’ Contract (3 Months)
Start Date
β’ Immediate
Experience Required
β’ 10+ years in Data & AI / Applied AI Engineering
Key Skills
β’ LLMs
β’ agentic AI
β’ AI system design
β’ RAG architectures
β’ vector databases
β’ cloud platforms: Azure, AWS, or GCP
β’ AI governance, ethics, and regulatory frameworks
β’ multi-agent systems
β’ orchestration frameworks
β’ data engineering
β’ data governance
β’ designing scalable, secure AI solutions
β’ stakeholder management
β’ executive communication skills
β’ mentoring and leading AI capability development
Responsibilities
β’ Define and contribute to AI strategy, roadmap, and governance frameworks
β’ Lead enterprise assurance for high-risk AI systems and conduct deep technical reviews
β’ Act as SME for AI technologies including LLMs and agentic AI
β’ Design and evaluate multi-agent systems (memory, planning, orchestration, autonomy controls)
β’ Lead PoCs for advanced AI workflows and semi-autonomous systems
β’ Define enterprise AI patterns (RAG, vector search, prompt governance, orchestration)
β’ Provide technical advisory on model selection, prompting strategies, and architecture trade-offs
β’ Establish AI standards, guardrails, and reusable frameworks
β’ Drive AI enablement through tooling, accelerators, and evaluation frameworks
β’ Mentor teams and uplift AI capability across the organization
β’ Ensure strong data foundations (data quality, lineage, governance, privacy)
β’ Challenge vendor solutions through benchmarking and risk assessment
Qualifications
β’ Experience in financial services or regulated industries
β’ Exposure to enterprise-scale transformation programs
β’ Strong commercial awareness and business case support
β’ Strong communication and stakeholder influence
β’ Strategic thinking with execution focus
β’ Ability to operate in ambiguous, fast-paced environments
β’ Problem-solving mindset with high ownership






