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Role Overview

Key Responsibilities

• Use case technical ownership: 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.
• 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.
• Confidence calibration and HITL thresholds: Lead AI Metric Baselines calibration; measure ECE, derive HITL routing thresholds empirically, and present recommendations to business and risk teams.
• Test strategy ownership: Own and execute the full AI IDP Test Strategy for your use cases across all testing bands through to sign-off.
• Agent Regression Testing: Maintain Golden and Regression Datasets; configure CI/CD regression pipeline gates; review results after every model or prompt change.
• Mentoring and code review: Mentor AI Engineers; conduct substantive technical code reviews of agent graphs, prompts, and MCP tool implementations; maintain coding standards.
• Stakeholder engagement: Present model quality metrics, STP rates, and HITL rates to business owners; recommend threshold adjustments with data-backed rationale.
• New capability adoption: Evaluate and prototype new AI capabilities for incorporation into the AWA accelerator catalogue.

Required Skills & Qualifications

• 5+ years Python development; 2+ years in production AI/ML engineering.
• Deep LangGraph or equivalent agentic framework experience: graph topology, state management, conditional edges, checkpoint-based recovery.
• LLM evaluation expertise: F1 measurement, Expected Calibration Error (ECE), hallucination detection, confidence calibration.
• Prompt engineering at scale: versioned prompts, sensitivity analysis, few-shot dataset curation.
• RAG architecture: hybrid retrieval (BM25 + vector), re-ranking, chunk citation, grounding verification.
• Azure AI Foundry or equivalent LLM inference platform: token budget management and APIM integration.
• Workflow orchestration: Orkes Conductor or Temporal — HITL wait tasks, retry policies, compensating transactions.
• CI/CD pipeline integration for ML: Azure DevOps, MLflow experiment tracking, model registry promotion.
• Bachelor's degree in Computer Science, AI/ML, or equivalent; Master's preferred.

Preferred Attributes

• Computer vision model deployment and evaluation experience.
• Azure AI Document Intelligence: form recogniser, custom models, layout analysis.
• Kubernetes / AKS: workload identity, namespace isolation, KEDA autoscaling.
• Banking domain knowledge: cheque clearing, trade finance, KYC, AML.
• Azure AI Engineer Associate or equivalent certification.
• Demonstrable production AI deployments with case studies or public work.

Halian Group: With over 28 years of experience, we have come to understand that innovation is the only way to provide agile, practical solutions that transform businesses and careers. Our resourcing and smart services help you to realise tomorrow's potential. Discover the amazing things possible when you bring the right people and the right technologies together. At Halian, we recognise that diversity, equity, and inclusion (DEI) are essential to building high-performing teams for our clients. We are committed to connecting organisations with top talent from all backgrounds, ensuring that every individual feels valued, respected, and empowered to contribute their unique perspectives. We encourage applications from all qualified candidates, regardless of race, gender, disability, or any other characteristic that makes them unique. #LI-CC1