Senior AI Engineer
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Key skills for this role
About the Role
Fecundity Technologies is seeking a Senior AI Engineer to lead technical delivery of AI use cases end-to-end. The role involves designing LangGraph agent graphs, confidence calibration, test strategy, and mentoring.
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 process: measure ECE, derive HITL routing thresholds
- Own and execute full AWA IDP Test Strategy for use cases
- Maintain Golden Dataset and Regression Dataset; configure CI/CD regression pipeline gates
- Mentor AI Engineers; conduct technical code reviews of agent graphs, prompts, and MCP tool implementations
- Present model quality metrics, STP rates, and HITL rates to Ops leads and business owners
- Evaluate and prototype new AI capabilities for incorporation into AWA 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: versioned prompts, sensitivity analysis, few shot dataset curation
- 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; Master's preferred
- Azure AI Engineer Associate or equivalent certification
Full Job Posting
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.
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 and code review: Mentor AI Engineers; conduct substantive technical code reviews of agent graphs, prompts, and MCP tool implementations; maintain AWA coding standards.
- Stakeholder engagement: Present model quality metrics, STP rates, and HITL rates to Ops leads and business owners; recommend threshold adjustments with data backed rationale.
- New capability adoption: Evaluate and prototype new AI capabilities (new Azure AI Foundry models, new LangGraph features, new RAG patterns) for incorporation into the AWA accelerator catalogue.
Required Skills and Experience
- 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 against ground truth, Expected Calibration Error (ECE), hallucination detection, confidence calibration
- Prompt engineering at scale: versioned prompts, sensitivity analysis, few shot dataset curation, PMS governance
- RAG architecture: hybrid retrieval (BM25 + vector), re ranking, chunk citation, grounding verification
- Azure AI Foundry or equivalent LLM inference platform: PTU, PAYG, token budget management, 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
Technical — Advantageous
- Computer vision model deployment and evaluation (object detection — TPR/TNR/IoU)
- Azure AI Document Intelligence: form recogniser, custom models, layout analysis
- Kubernetes / AKS: workload identity, namespace isolation, KEDA autoscaling
- Apache Iceberg, DuckDB, and 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 or equivalent certification
- Demonstrable production AI deployments — case studies or public work highly valued
Pay
- AED21,000.00 AED30,000.00 per month
Work Location
- In person
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