Agentic AI Engineer
Posted 5 days ago by iBSC
Negotiable
Inside
Hybrid
Manchester, UK
Summary: The role of Agentic AI Engineer involves working with a large consultancy on a 6-month contract inside IR35, based in Manchester. The position requires a blend of on-site and remote work, specifically 3 days on-site and 2 days remote. The ideal candidate should possess extensive experience in architecting AI solutions, particularly in regulated environments, and have a strong background in Generative AI platforms.
Key Responsibilities:
- Architect enterprise-scale Generative AI platforms in regulated environments.
- Design secure, scalable AI solutions and operating models across multi-cloud and hybrid estates.
- Implement MLOps frameworks and delivery governance from strategy to production.
- Manage compliance and enterprise standards related to AI solutions.
- Oversee Cloud Architecture across GCP, Azure, and AWS.
- Utilize AI DevOps/MLOps practices including CI/CD and model versioning.
- Conduct programme planning, risk management, and stakeholder alignment.
- Handle Data & Analytics tasks including ETL/ELT and data quality management.
Key Skills:
- Strong experience as an AI Architect.
- Expertise in AI/ML based agentic AI solutions.
- Proven experience in architecting Generative AI platforms.
- Knowledge of MLOps frameworks and delivery governance.
- Familiarity with multi-cloud environments (GCP, Azure, AWS).
- Experience in AI DevOps/MLOps practices.
- Strong data analytics skills including ETL/ELT and SQL.
Salary (Rate): undetermined
City: Manchester
Country: UK
Working Arrangements: hybrid
IR35 Status: inside IR35
Seniority Level: undetermined
Industry: IT
Agentic AI Engineer
My client, a large consultancy, is in need of an Agentic AI Engineer for a 6 month contract opportunity inside IR35 based in Manchester offering 2 days per week remote but requiring 3 days per week on-site.
The ideal candidate will have strong experience as an AI Architect with good Experience across AI/ML based agentic AI solutions and good experience architecting enterprise-scale Generative AI platforms in regulated environments, Strong in designing secure, scalable AI solutions and operating models across multi-cloud and hybrid estates-selecting services based on client constraints, risk posture and total cost, Proven in MLOps frameworks, delivery governance from strategy to production, compliance and enterprise standards, Generative AI & LLM Architecture: RAG systems, embeddings, prompt orchestration, tool/function calling, evaluation, safety/guardrails, Cloud Architecture (multi-cloud): GCP (Vertex AI, BigQuery, GKE), Azure (Azure OpenAI, Azure ML, AKS), AWS (SageMaker, Lambda, API Gateway), AI DevOps/MLOps: CI/CD, Terraform/IaC, model & prompt versioning, LLM evaluation (LLM-as-Judge, RAGAS), monitoring/observability (Langfuse), cost optimisation, Delivery Governance: programme planning, roadmap ownership, risk & dependency management, stakeholder alignment, executive reporting and Data & Analytics: Data lakes/warehouses, ETL/ELT, PySpark, SQL, BI integration, data quality and lineage.