Head of AI Engineering - NCT

banyansoftware; USA; Remote; USD 180.000 - 240.000; Vollzeit

Benefits dieser Stelle

Remote work

Autonomy on AI strategy

Leadership peer network

Zusammenfassung

BanyanSoftware in the United States is seeking a hands-on builder-to-leader who will start by drafting and shipping the first AI capabilities for a 15-year-old county-level case-management platform, then scale into engineering leadership as patterns prove reliable.

The role is remote in the US, with strict compliance requirements for public-sector work; you will refactor legacy components, orchestrate RAG systems, and mentor a team while partnering with the CEO on acceleration of localized

Qualifikationen

• 8+ years of hands-on software engineering with modernizing architectures.
• End-to-end AI/ML systems deployed to real users with data pipelines.
• Founding/first AI engineer with independent baseline architecture delivery.
• Judgment on build-versus-buy for a Microsoft-stack modernization.
• Proven leadership in growing engineering teams and mentoring talent.
• US-based with eligibility for government-adjacent compliance.

Aufgaben

• Design and ship foundational AI capabilities (RAG, code generation, LLM orchestration).
• Refactor legacy components into scalable, cloud-native services.
• Deliver features safely using feature flags and monitoring under HIPAA/CJIS.
• Lead delivery accountability, mentor developers, set engineering rhythms.
• Partner with the CEO on AI strategy and cross-group initiatives.

Kenntnisse

AI/ML system design

Cloud-native / DevSecOps

Team leadership / mentoring

Legacy modernization

RAG systems

AI governance

Tools

Azure ML

Azure OpenAI

LLM orchestration

Code generation

Distributed systems

Jobbeschreibung

Role overview

This is a hands-on builder-to-leader role leading the transition of a 15-year-old case-management platform used in county-level Health and Human Services operations into an AI-first product. The position begins with a strict build-solo mandate, personally designing and shipping the first version of foundational AI capabilities, then evolves into engineering leadership as the team is scaled around proven patterns. It is US-based and remote, with eligibility requirements tied to government-adjacent public-sector compliance work.

Responsibilities

• Personally design and build foundational AI capabilities such as RAG systems, code generation, LLM orchestration, and multi-agent workflows that analyze legacy code and produce production-ready services.
• Refactor legacy components into scalable, cloud-native services and replace manual workflows with AI-driven automation, avoiding any temptation toward a wholesale platform rewrite.
• Ship features safely using feature flags, shadow mode, and monitoring while operating within HIPAA and CJIS compliance frameworks.
• Once the AI factory is proven solo, take on direct delivery accountability: managing execution, raising talent density, setting engineering rhythms, and mentoring developers into an AI-native way of working.
• Act as the core technical partner to the CEO while coordinating with a broader group-level AI initiative to accelerate localized product value.

Requirements

• 8+ years of hands-on software engineering with a track record of modernizing complex architectures and establishing cloud-native or DevSecOps practices.
• Documented history of shipping functional AI/ML systems end-to-end to real users, including data pipelines, modeling, deployment, and monitoring.
• Experience operating as a founding or first AI engineer, comfortable delivering baseline architecture independently before relying on a large team.
• Strong judgment on build-versus-buy and the patience to guide a long-established Microsoft-stack platform through a phased modernization.
• Proven engineering team management experience and a genuine orientation toward developing technical talent.
• US-based with full eligibility for government-adjacent and public-sector compliance work.

Nice to have

• Direct GovTech, public-sector, or federal case-management software experience.
• Familiarity with the Microsoft AI stack, including Azure ML and Azure OpenAI integrations.
• Experience coordinating with distributed or offshore engineering teams.

Benefits and work setup

• Long-horizon environment focused on permanent ownership rather than short exit cycles, paired with autonomy over AI strategy, tooling, and execution.
• Access to a broader peer network of operating-company leaders sharing modernization playbooks and lessons.