AI SDLC Engineer integrating modern AI tooling into the full Software Development Life Cycle at Quento Technologies S.A. Collaborating with teams to enhance product development and delivery.
About the role
- AIML Director responsible for defining AI strategy and leading engineering teams at Credit Acceptance. Driving enterprise-level architecture, operational excellence, and generative AI innovations.
Responsibilities
- Define and communicate the long-term vision for Generative AI and platform capabilities
- Partner with senior executives, product, and engineering leaders to prioritize initiatives and allocate resources effectively
- Lead the enterprise-level architectural design and technical strategy for major components of our generative AI applications and platform
- Partner with senior engineering managers, product leaders, and data scientists / MLEs to translate strategic objectives into executable architectural blueprints
- Drive the adoption of superior engineering standards and advanced AI evaluation frameworks like LangSmith
- Spearhead technical solutioning for the platform's most complex challenges
- Mentor and cultivate a team of associate architects and senior engineers
- Own and execute a significant portion of the technology roadmap
- Oversee design and deployment of enterprise-scale GenAI platforms, inference pipelines, and AI-powered applications
- Ensure operational excellence in LLM Ops, including automation, observability, and lifecycle management
- Champion adoption of cutting-edge generative AI techniques
Requirements
- PhD in Computer Science, AI, or related field with 10+ years in AI/ML engineering (preferred); or MS with 12+ years of experience
- Minimum 5 years in senior leadership roles managing managers and large engineering teams
- Proven track record in building enterprise level production-grade GenAI platforms and services and strong problem-solving skills
- In-depth knowledge and hands-on experience with LLM fine-tuning, model optimization, context graphs, automation, and advanced prompting strategies
- Deep knowledge of LLM lifecycle tools, distributed systems, and cloud-native architectures
- Architect and implement enterprise-grade LLM-powered solutions, managing the full lifecycle from business requirements to production deployment, monitoring, and continuous optimization
- Design and develop multi-agent GenAI systems using state-of-the-art frameworks (LangChain, LlamaIndex) to orchestrate complex workflows across retrieval augmentation, data operations, and compliance verification
- Engineer robust Retrieval Augmented Generation (RAG) pipelines incorporating advanced techniques such as hybrid retrieval, reranking, query expansion, and contextual compression
- Implement parameter-efficient fine-tuning strategies (LoRA, QLoRA, PEFT) to adapt foundation models to domain-specific use cases while optimizing for inference costs and latency
- Develop intelligent routing and orchestration systems to manage conversation state across multiple specialized AI agents, ensuring seamless transitions between different system capabilities
- Build evaluation frameworks to measure and improve LLM performance across diverse metrics, including factuality, coherence, task completion, and alignment with business objectives
- Integrate LLM solutions with existing enterprise architecture, ensuring compliance with data security policies, authentication mechanisms, and transaction safety requirements
Benefits
- Excellent benefits package that includes 401(K) match
- Adoption assistance
- Parental leave
- Tuition reimbursement
- Comprehensive medical/ dental/vision
- Many nonstandard benefits that make us a Great Place to Work
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