About the role

  • Design & build AI applications: deliver end‑to‑end LLM and ML solutions (chat/agent experiences, RAG pipelines, workflow automation), from discovery and data prep to deployment and monitoring.
  • Develop task‑specific agents & copilots: create secure copilots for internal teams using Copilot Studio and integrate with business systems (e.g., Dynamics 365, SharePoint, Microsoft 365).
  • Integrate with our AI data lake: implement retrieval, embeddings, vector indexing, and guardrails, ensuring high‑quality grounding for LLMs and auditable outputs.
  • Productionize responsibly: apply MLOps/GenAIOps (experiment tracking, model registry, CI/CD, telemetry, model & prompt evaluation, rollback strategies) with cost, latency, and safety in mind.
  • Security, risk & compliance: build with least‑privilege, data‑loss prevention, PII protection, and policy alignment (auditability, content filtering, red‑teaming).
  • Cross‑functional collaboration: partner with onboarding, compliance, sales/CRM, and treasury to translate problems into deployable AI solutions with measurable outcomes.
  • Engineering excellence: write clear design docs/RFCs, participate in design & code reviews, and contribute to shared components, templates, and internal best practices.

Requirements

  • 3–7 years of experience in software engineering, AI/ML, or data-driven product development
  • Hands-on experience with Microsoft Copilot, Copilot Studio, or similar GenAI platforms
  • Strong understanding of LLMs, prompt engineering, and responsible AI principles
  • Experience working with enterprise systems (e.g., CRM, KYC platforms, workflow tools)
  • Excellent problem-solving, communication, and stakeholder management skills
  • Ability to thrive in a fast-paced, ambiguous environment

Job title

AI Engineer

Job type

Experience level

Mid levelSenior

Salary

Not specified

Degree requirement

No Education Requirement

Location requirements

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