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
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