Senior AI Engineer (m/f/d)
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Key skills for this role
About the Role
Halian is seeking a Senior AI Engineer to take end-to-end technical ownership of agentic automation use cases within a UAE financial institution's AI Centre of Excellence. The role involves leading LangGraph multi-agent pipelines, confidence calibration, and mentoring AI Engineers.
Key Skills for This Role
Responsibilities
- Own technical delivery of AWA use cases from discovery through production
- Design LangGraph agent graph topologies for complex multi agent pipelines
- Lead AI Metric Baselines calibration and derive HITL routing thresholds
- Own and execute the full AI IDP Test Strategy for use cases
- Maintain Golden and Regression Datasets; configure CI/CD regression pipeline gates
- Mentor AI Engineers and conduct technical code reviews
- Present model quality metrics to business owners and recommend threshold adjustments
- Evaluate and prototype new AI capabilities for incorporation into the accelerator catalogue
Requirements
- 5+ years Python development; 2+ years in production AI/ML engineering
- Deep LangGraph or equivalent agentic framework experience
- LLM evaluation expertise: F1, ECE, hallucination detection, confidence calibration
- Prompt engineering at scale
- RAG architecture: hybrid retrieval, re ranking, chunk citation, grounding verification
- Azure AI Foundry or equivalent LLM inference platform
- Workflow orchestration: Orkes Conductor or Temporal
- CI/CD pipeline integration for ML: Azure DevOps, MLflow
- Bachelor's degree in Computer Science, AI/ML, or equivalent
Full Job Posting
Role Overview
- We are seeking a Senior AI Engineer to take end to end technical ownership of one or more agentic automation use cases within a leading UAE financial institution's AI Centre of Excellence.
- You will lead the delivery of complex LangGraph multi agent pipelines, drive confidence calibration and HITL threshold strategy, and mentor AI Engineers across the team.
- This is a hands on leadership role where you define architecture within your domain, identify production failure modes early, and advance the adoption of new AI capabilities across a growing use case portfolio.
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.
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