Principal AI Platform Engineer

Compeer Financial•Rochester, NY

22h•$133,000 - $180,000•Hybrid

About The Position

Compeer Financial is a member-owned cooperative supporting agriculture and rural communities. This role is the highest-level individual contributor in the software engineering career framework, providing enterprise technical leadership with a focus on leading and expanding responsible AI use across the organization. The Principal AI Platform Engineer sets the enterprise AI Enablement Platform direction, connects AI technology strategy to enterprise needs and risks, and advances AI-enabled engineering and Agentic AI at scale. The incumbent serves as a trusted advisor to senior leadership, builds enterprise AI tools and platforms, and fosters an engineering culture centered on responsible AI adoption and operational excellence.

Requirements

Bachelor's degree in Computer Science, Software Engineering, or related discipline, or equivalent experience.
Extensive experience designing, building, and operating complex, business-critical software, distributed systems, and platforms.
Hands-on experience designing and building AI applications and platforms using LLMs, retrieval-augmented generation, vector search, agent orchestration, Model Context Protocol, and cloud AI services such as Azure OpenAI or Azure AI Foundry.
Experience scaling responsible AI-enabled engineering and Agentic AI across the software lifecycle, prompt and model versioning, quality and safety testing, cost and performance monitoring, production support, and validation of AI-generated outcomes.
Working knowledge of responsible AI and AI governance, model and vendor risk management, privacy, bias and fairness, auditability, human oversight, sensitive-data protection, and translating governance requirements into practical technical controls.
Experience leading complex solution design and strategic technical decisions across multiple portfolios, products, systems, or business domains.
Distinguished software engineering expertise across application development, APIs and integration, cloud-native and event-driven architectures, data, security, platforms, DevSecOps, testing, CI/CD, observability, reliability, and operational excellence.
Ability to analyze highly complex problems, anticipate second- and third-order effects, and balance technical, security, regulatory, operational, and investment trade-offs.
Exceptional communication, influence, leadership, and learning agility.

Nice To Haves

Experience in financial services, agriculture, or another regulated industry.

Responsibilities

Leads AI platform engineering and adoption by building enterprise AI platforms, tools, services, and integrations for LLMs, retrieval-augmented generation, vector search, agents, Model Context Protocol, and AI-assisted and agentic software development.
Establishes AI operational excellence through reusable components and guardrails, evaluation frameworks, monitoring, cost and performance management, output validation, production support, and responsible scaling of AI tools and agents.
Partners on AI governance and risk with Risk Management, Information Security, Legal, Compliance, and Data Governance, translating requirements into access controls, data protection, model and vendor risk management, human oversight, auditability, and use-case risk tiering.
Owns AI-enabled and Agentic AI engineering delivery for the most strategic and ambiguous software initiatives from discovery through sustained operation.
Develops engineers and technical leaders through mentoring, communities of practice, training, and reusable guidance on AI-assisted development, prompt and context engineering, responsible AI, agentic development, and critical evaluation of AI-generated output.
Advances technical mastery and engineering excellence across architecture, distributed systems, integration, cloud-native engineering, DevSecOps, testing, CI/CD, security, observability, and reliability.
Connects engineering to business outcomes by translating strategy, client needs, regulatory obligations, and risk into engineering strategies, investment options, build-versus-buy decisions, and multi-year roadmaps.
Leads across organizational boundaries by partnering with engineering, architecture, product, security, data, operations, quality, risk, and business leaders.