Senior AI/ML Engineer

Posted 4ds ago

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Job Description

Senior AI/ML Engineer at Aubrant Digital building AI capabilities for client engagements. Collaborating with Technical Leads and engineers to create accurate, auditable AI workflows.

Responsibilities:

  • Build reusable AI skills consumed across engagements: Document Intelligence, document summarization, data normalization, anomaly detection, matching engines, and compliance test runners
  • Design and train custom Document Intelligence neural models for client-specific document types
  • Implement RAG over enterprise document libraries using Azure AI Search with hybrid vector + keyword retrieval and semantic ranking
  • Build LLM reasoning chains using Azure OpenAI (GPT-4o for complex reasoning, GPT-4o-mini for high-volume classification) with prompt versioning and guardrails
  • Design agent orchestration in Azure AI Foundry for multi-step workflows: extract, search, reason, and generate output with tool-use grounding
  • Build evaluation harnesses, accuracy thresholds, and drift detection; tie outputs to confidence-gated HITL review tiers
  • Implement audit trail patterns for AI-assisted workloads: prompt/response logging, evidence chains, and SOC 2 aligned event sourcing
  • Mentor engineers on prompt engineering, RAG design, agentic patterns, and evaluation; contribute to Aubrant's AI engineering standards

Requirements:

  • Bachelor's Degree in Computer Science, Machine Learning, or a related discipline, or equivalent experience
  • MUST be proficient in written and spoken English (85%)
  • 5 to 8 years of professional engineering experience with at least 3 years building production AI / ML systems
  • Expert-level proficiency in Azure AI services , including Azure OpenAI (GPT-4o, GPT-4o-mini, PTU and token-based billing), Azure AI Foundry, Document Intelligence (custom neural models), and AI Search
  • Expert-level proficiency in RAG and agent design , including hybrid retrieval, semantic ranking, prompt versioning, guardrails, evaluation harnesses, and confidence-aware HITL design
  • Strong proficiency in Python for AI/ML development
  • Hands-on experience with Document Intelligence custom models
  • Experience designing AI workflows for regulated environments
  • Working knowledge of Medallion data architecture, vector databases, and embedding pipelines
  • Solid Git, code review, and engineering standards discipline; experience with trunk-based development and IaC for AI deployments
  • Experience in financial services, professional services, or other regulated industries is a plus
  • Experience with .NET interop or polyglot AI service ecosystems is a plus

Benefits:

  • Flexible work arrangements
  • Professional development