AI Platform Engineer

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NOVA Corporation

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Technology • B2B • SaaS

NOVA Corporation is a leading provider of advanced technological solutions aimed at enhancing efficiency and productivity across various sectors. With a strong focus on innovation, NOVA Corporation develops cutting-edge software and hardware products that serve business and consumer markets alike. The company's mission is to empower organizations with the tools they need to succeed in a rapidly changing digital landscape.

2 - 10 employees

Founded 1999

🤝 B2B

☁️ SaaS

📋 Description

• Design and Implement AI Workflows • Lead the design and deployment of enterprise-grade AI workflows using the Stack AI platform’s visual builder interface. • Construct dynamic pipelines that integrate large language models (LLMs), retrieval mechanisms, enterprise data sources, and multi-step business logic. • Architect solutions that address complex tasks such as document summarization, structured content generation, data-driven decision support, and automated process flows. • Ensure workflows follow modular design principles, are testable, maintainable, and compatible with DDC’s configuration and deployment lifecycle standards. • Develop and Orchestrate Agentic AI Solutions • Build autonomous AI agents that perform goal-directed reasoning, access tools and APIs, retrieve contextual information, and coordinate multi-step actions aligned to defined outcomes. • Implement robust retrieval-augmented generation (RAG) pipelines to ensure agents can access accurate, relevant, and timely knowledge from across DDC’s structured and unstructured data stores. • Design agents that address use cases ranging from proposal assembly to compliance automation, while incorporating fault handling, validation checkpoints, and human-in-the-loop controls to ensure reliability, auditability, and mission alignment. • Establish Platform Standards, Patterns, and Design Governance • Define and institutionalize platform-wide standards for agent development, including naming conventions, workflow patterns, versioning practices, interface expectations, and logic design rules. • Curate and maintain a reference library of approved agentic design patterns and solution blueprints for use across departments. • Document prompt and context engineering guidelines, RAG implementation templates, retry strategies, validation frameworks, and ethical decision logic. • Promote reusable design across workflows, reducing duplication, increasing maintainability, and ensuring interoperability across agents built within DDC’s Agentic AI Infrastructure.

🎯 Requirements

• Minimum 3 years of professional experience in software development, data engineering, AI engineering, or a similar technical role supporting enterprise-scale systems. • At least 1 year of hands-on experience building and shipping generative AI applications or retrieval-augmented generation (RAG) systems that operated in real user-facing environments. • Experience must include designing workflows, using modern LLMs, integrating data sources, and solving practical AI delivery challenges. • Demonstrated experience owning the lifecycle of AI-driven solutions from concept through deployment. • Candidates should be able to provide a portfolio, demonstration artifacts, GitHub repositories, or equivalent examples of real AI systems such as chat assistants, workflow agents, knowledge tools, data extraction pipelines, or proposal-support agents. • Experience working with enterprise architectures, ideally including business processes, data architectures, content repositories, and application ecosystems. • Familiarity with environments where data is fragmented or inconsistent, and the ability to design AI workflows that operate effectively despite technical debt or process gaps.

🏖️ Benefits

• Paid time off • Professional development opportunities