As an experienced AI Engineer, you will design, build, and deploy production-grade AI solutions that bridge experimental machine learning with scalable software engineering. In this replacement role, you will play a critical role in enabling enterprise-ready AI capabilities with a strong focus on large language models (LLMs), retrieval-augmented generation (RAG), and agentic workflows, operating within established governance frameworks.
Requirements
- Design, build, and deploy robust, scalable, production-grade AI applications using frameworks such as LangChain, LlamaIndex, AutoGPT, and related LLM orchestration tools.
- Develop, refine, and optimize complex prompt strategies; manage model context windows; and fine-tune models where required to maximize performance, accuracy, and cost efficiency.
- Integrate AI capabilities into existing enterprise environments through RESTful APIs, microservices, and cloud-native architectures.
- Build, maintain, and optimize vector databases (e.g., Pinecone, Milvus, Weaviate) and design efficient data ingestion and embedding pipelines to support retrieval-augmented generation (RAG) solutions.
- Monitor AI systems in production and proactively address issues related to hallucinations, latency, reliability, scalability, and token-cost optimization.
- Collaborate closely with AI Architects, AI Studio Leads, ML Engineers, Data Scientists, Full-Stack Developers, Service Line Labs, and Citizen Developers on firm-wide initiatives and internal platforms.
- Support AI system documentation, lifecycle management, and control processes in alignment with ISO/IEC 42001 enterprise governance requirements.
- Adhere to established AI risk management, data governance, and security policies, and assist with model inventories, traceability, and change-management activities.
- Participate in model testing and validation activities in accordance with the NIST AI Risk Management Framework, including mapping and measuring model risks.
- Support the implementation of risk-mitigation controls and ongoing monitoring, and follow governance processes that promote transparency, accountability, and responsible AI use.
Benefits
- Competitive total cash compensation
- Flexible benefits
- Market leading personal time off policy
- Wellness initiatives reimbursement
- Inclusive and engaging work environment
- Learning and professional development opportunities
- Diversity, Equity and Inclusion initiatives
