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AI Architect

Job in London, Greater London, W1B, England, UK
Listing for: Vallum Associates
Full Time position
Listed on 2026-09-01
Job specializations:
  • Software Development
    AI Engineer (Applied/Software)
Salary/Wage Range or Industry Benchmark: 530 - 600 GBP Daily GBP 530.00 600.00 DAY
Job Description & How to Apply Below
Role: AI Architect

Location:

London, UK

(Exp Range 12+)

Type of work:
Contract

Mode of work:
Hybrid 2 days Onsite in week

JD:

Essential skills/knowledge/experience:

* Design agentic AI architectures using multi‑agent orchestration patterns (planner‑executor, supervisor‑worker, tool‑using agents).

* Define reference architectures for enterprise agent platforms integrating LLMs with systems of record (core banking, CRM, risk, payments).

* Select and standardize frameworks (e.g., Lang Graph, Google ADK, MCP, A2A patterns).

* Hands‑on expertise with agentic frameworks (orchestrators).

* Experience with LLMs, prompt engineering, tool/function calling, memory management.

* Exposure to AI quality metrics: task success rate, groundedness, containment, FCR.

* Experience on Google Cloud Platform (preferred) or equivalent hyperscale.

* Deep understanding of LLMs, generative AI, RAG patterns, vector databases, embeddings, and prompt/guardrail engineering.

Desirable skills/knowledge/experience:

* Build Production Grade Agentic AI applications and necessarily have navigated through security, governance and performance management of the end to end model.

* Hands-on expertise on MLOps / Agent Ops, CI/CD, and observability.

* Strong understanding of regulated financial services environments.

* Proven experience implementing AI risk controls, model governance, and auditability.

* Ensure alignment with FCA, PRA, data privacy, model risk management, and LBG internal policies.

* Knowledge of banking processes: retail banking, lending, payments, compliance.

* Strong experience designing end‑to‑end AI/ML architectures, including data ingestion, feature engineering, model training, deployment, and monitoring.

* Hands‑on expertise with cloud AI platforms (GCP).

* Strong knowledge of LLMOps practices, including CI/CD for models, model registries, feature stores, lineage tracking, and observability.

* Experience architecting scalable real‑time, batch, and streaming inference systems with clear performance and reliability requirements.

* Familiarity with secure cloud patterns, IAM, VPC design, and data protection
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