AI Engineer

LATENT CAPITAL LLC
New York, NY, United States
15 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Working hours
Regular working hours

Tech stack

.NET Framework Artificial Intelligence Microsoft Azure Data Intelligence Systems Architecture Data Processing Cloud Platform System Snowflake IT Architecture Backend Build Management AngularJS
+3 more
Data Management Front End Software Development Databricks

Job description

  • Design and build AI-assisted features and agentic workflows on Azure AI Foundry.

  • Develop domain-specific Micro UI applications using Angular, integrated with .NET backend services.

  • Implement document intelligence pipelines to extract, process, and structure data from unstructured documents.

  • Work with Data bricks and Snowflake for backend data processing, storage, and retrieval supporting AI features.

  • Apply agentic coding practices and AI-assisted development tooling as a core part of the delivery workflow (target: 60%+ of code AI-generated, with rigorous human review).

  • Collaborate with architects, business analysts, and domain teams to align each Micro UI to its specific domain’s access patterns and requirements.

  • Contribute to platform engineering standards ensuring Micro UIs are consistent, secure, and maintainable across domains., This engagement requires seasoned resources who have previously delivered similar work - not first-time exposure. Successful candidates will be able to speak concretely to past projects involving agentic AI development, Micro UI/micro-frontend delivery, and backend document intelligence at scale. Potential Role Variants on This Engagement

  • AI Engineering, * Design and build AI-assisted features and agentic workflows on Azure AI Foundry.

  • Develop domain-specific Micro UI applications using Angular, integrated with .NET backend services.

  • Implement document intelligence pipelines to extract, process, and structure data from unstructured documents.

  • Work with Databricks and Snowflake for backend data processing, storage, and retrieval supporting AI features.

  • Apply agentic coding practices and AI-assisted development tooling as a core part of the delivery workflow (target: 60%+ of code AI-generated, with rigorous human review).

  • Collaborate with architects, business analysts, and domain teams to align each Micro UI to its specific domain’s access patterns and requirements.

  • Contribute to platform engineering standards ensuring Micro UIs are consistent, secure, and maintainable across domains.

Requirements

We are seeking an experienced AI Engineer to join a platform engineering initiative focused on building Micro UIs - independently deployable, domain-scoped front ends - across a broader enterprise platform. The role blends applied AI engineering (Azure AI Foundry, agentic development patterns) with modern full-stack delivery (.NET, Angular) and backend document/data intelligence work (Databricks, Snowflake). This is a seasoned-resource engagement: candidates should have prior, demonstrable experience delivering this type of work, not solely theoretical familiarity., * Hands-on experience with Azure AI Foundry (or direct equivalent Azure AI/ML tooling).

  • .NET backend development experience.

  • Angular front-end development experience.

  • Experience working with backend document processing/data platforms - Databricks and Snowflake.

  • Demonstrated experience with agentic AI development and AI-assisted (‘agentic’) coding workflows, with a track record of significant AI-generated code (60%+) in production delivery.

  • Prior experience building Micro UI / micro-frontend architectures, ideally with domain-based access segmentation.

  • Strong communication skills; able to clearly articulate prior relevant project experience during client-facing evaluation.

Preferred / Complementary Experience

  • AI architecture experience - designing AI-first system architectures, not just implementing features.

  • Document intelligence specialisation (OCR, extraction, classification, unstructured-to-structured pipelines).

  • Platform engineering background (shared services, internal developer platforms, golden paths).

  • Business analysis experience translating domain requirements into technical specifications.

  • Project / program management experience on similar AI or platform modernization engagements.

  • Domain-specific engineering experience relevant to the client’s industry.

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