AI Platform Engineer
Posted 105ds ago
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Job Description
AI Engineer responsible for designing, developing, and deploying AI solutions on DDC’s Stack AI platform. Collaborate within DDC’s AI-First transformation to deliver value to clients.
Responsibilities:
- 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.
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:
- Health insurance
- 401(k) matching
- Paid time off
- Professional development opportunities
- Flexible work hours

















