Bachelor's or Master's degree in Computer Science, AI, Machine Learning, or a related quantitative field
6+ years of experience in software engineering and/or data science, with at least 4+ years in a technical leadership or architecture role focused on AI/ML
Deep understanding of AI agent architectures, including concepts like planning, memory, and tool integration (e.g., ReAct, RAG, MCP)
Expertise with the AI/ML ecosystem, including LLM application and agentic frameworks (e.g., LangChain, LlamaIndex, Semantic Kernel)
Proven full-stack experience designing scalable, services-oriented architectures on a major cloud platform (e.g., AWS, GCP)
Strong proficiency in core programming languages used in AI/ML (e.g., Python)
Excellent analytical and problem-solving skills, with the ability to navigate ambiguity and design elegant solutions for complex technical challenges
Preferred Qualifications
Deep familiarity with Decision Science disciplines like optimization, simulation, and advanced forecasting
Experience designing solutions for multi-tenant platforms or two-sided marketplaces
Hands-on experience with enterprise MLOps/LLMOps tools and principles
Experience with knowledge graphs and semantic technologies
Responsibilities
Design and own the solution architecture for DDSI's AI/ML solutions, including multi-step agentic workflows, RAG patterns for structured and unstructured data, and MCP-based "smart specialist" services
Partner with Product Managers and business stakeholders to translate complex business needs into viable, scalable, and secure technical solution designs
Serve as the primary technical liaison between DDSI and the central AI Factory engineering teams, ensuring our solutions are architected for seamless integration and performance on the enterprise platform
Lead the technical evaluation of new AI frameworks, vendor platforms, and architectural patterns, conducting rapid proof-of-concept builds to prove feasibility and guide technical direction
Act as a hands-on technical expert and mentor, guiding engineering teams on best practices for building robust, reusable, and maintainable agentic systems
Create and maintain architectural documentation, including reference architectures and "cookbooks" that enable other teams to leverage DDSI's patterns and services
Identify and mitigate technical risks in the solution design phase, ensuring long-term scalability and alignment with enterprise technology standards
Skills
AI
ML
Generative AI
Solution Architecture
Agentic Workflows
RAG
Forecasting
Optimization
Product Management
Data Analytics
Statistical Modeling
Econometric Modeling
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