Senior AI Engineer
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About the Role
Job Title: Senior AI Engineer About the Role We're hiring for our esteemed financial sector client.
Key Skills for This Role
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About the Role
We're hiring for our esteemed financial sector client.
They are scaling their Agentic Workflow Automation (AWA) platform and hiring 8 Senior AI Engineers to lead the end-to-end technical delivery of real-world AI use cases — from initial architecture through to production sign-off.
This is a high-ownership, high-impact role.
You'll design and build complex multi-agent pipelines on LangGraph, own confidence calibration and Human-in-the-Loop (HITL) routing strategy, drive test sign-off, and mentor a team of AI Engineers.
Your decisions ship to production.
What You'll Own
- End-to-end technical delivery of one or more AWA use cases — from discovery through production
- LangGraph agent graph architecture: Supervisor-Worker fan-out, parallel execution, state compression, and cross-document reconciliation
- AI confidence calibration: measure Expected Calibration Error (ECE), derive HITL thresholds empirically, present recommendations to business and risk teams
- Full test strategy ownership across all four bands: Model/Prompt/Agent/Security, Adversarial, Integration, and UAT
- Golden Dataset and Regression Dataset maintenance; CI/CD regression pipeline gate configuration
- Technical mentoring and code review for AI Engineers
- Stakeholder reporting on model quality, STP rates, and HITL rates
- Prototyping and evaluating new AI capabilities for incorporation into the AWA accelerator catalogue
Essential
- 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, 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 experience
- Workflow orchestration: Orkes Conductor or Temporal (HITL wait tasks, retry policies, compensating transactions)
- CI/CD pipeline integration for ML: Azure DevOps, MLflow, model registry
- Nice to have:
- Computer vision model deployment and evaluation
- Azure AI Document Intelligence (form recogniser, custom models, layout analysis)
- Kubernetes / AKS (workload identity, KEDA autoscaling)
- Apache Iceberg, DuckDB, data contract patterns
- Banking domain knowledge: cheque clearing, trade finance, KYC, AML
Qualifications
- Bachelor's degree in Computer Science, AI/ML, or equivalent; Master's preferred
- Azure AI Engineer Associate certification or equivalent
- Demonstrable production AI deployments — case studies or public work highly valued
- Ready to apply?
- If you've shipped production AI systems, understand the gap between a demo and a reliable agent, and want real technical ownership — we'd love to hear from you.
- The company is ready to offer visa sponsorship for qualifying candidates.
- Apply below or reach out directly.
- We're interviewing now.
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