Senior AI Engineer
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Key skills for this role
About the Role
Start Date ASAP My client is a global data, AI, digital transformation, and consulting company that helps organisations use data and technology to improve business performance,.
Key Skills for This Role
Responsibilities
- Own the technical delivery of one or more AWA use cases from discovery through production
- Define Agent Profile, Use Case Manifest, Data Manifest, and Tool Authorisation Matrix for each use case
- Design LangGraph agent graph topologies for complex multi agent pipelines including Supervisor Worker fan out, parallel execution, state compression, and cross document reconciliation
- Lead AI Metric Baselines calibration process: measure ECE, derive HITL routing thresholds empirically, present recommendations, and own signed AI Metric Baselines table
- Own and execute the full AWA IDP Test Strategy for your use cases through sign off
- Maintain Golden Dataset and Regression Dataset; configure CI/CD regression pipeline gates; review regression results after every model or prompt change
- Mentor AI Engineers and serve as primary escalation point for complex LangGraph, LLM, and evaluation challenges
Requirements
- Experience leading technical delivery of agentic workflow automation use cases end to end
- Deep expertise in LangGraph agent graph topologies for complex multi agent pipelines
- Experience with confidence calibration and HITL threshold negotiation
- Ownership of test strategy including Model/Prompt/Agent/Security, Adversarial, Integration, and UAT testing bands
- Ability to maintain Golden Dataset and Regression Dataset for use cases
- Experience mentoring AI Engineers and acting as escalation point for complex challenges
Full Job Posting
Company Overview
- My client is a global data, AI, digital transformation, and consulting company that helps organisations use data and technology to improve business performance, customer experience, and decision making.
Role Overview
- The Senior AI Engineer leads the technical delivery of one or more AWA use cases end to end, from Agent Profile definition through to production UAT sign off. You own the architectural decisions within your use case domain: agent graph topology, confidence calibration, HITL threshold negotiation wit
Key Responsibilities
- Use case technical ownership: Own the technical delivery of one or more AWA use cases from discovery through production; define the Agent Profile, Use Case Manifest, Data Manifest, and Tool Authorisation Matrix for each use case.
- Architecture and design: Design LangGraph agent graph topologies for complex multi agent pipelines including Supervisor Worker fan out, parallel execution, state compression, and cross document reconciliation (3 way match).
- Confidence calibration and HITL thresholds: Lead the AI Metric Baselines calibration process: measure ECE, derive HITL routing thresholds empirically, present threshold recommendations to business and risk teams, and own the signed AI Metric Baselines table.
- Test strategy ownership: Own and execute the full AWA IDP Test Strategy for your use cases: all four testing bands (Model/Prompt/Agent/Security, Adversarial, Integration, UAT) through to sign off.
- Agent Regression Testing: Maintain the Golden Dataset and Regression Dataset for your use cases; configure CI/CD regression pipeline gates; review regression results after every model or prompt change.
- Mentoring: Mentor AI Engineers and act as primary escalation point for complex challenges.
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