Manager of talent acquisition with 10 years of experience in specialized recruiting areas. Qualifications: bachelor degree in computer science, artificial intelligence, machine learning, software engineering, or a related field. Minimum years of experience: 3 years preferred knowledge/skills: designing, training, and deploying machine learning models and large language models (llms) into production environments. Developing scalable, cloud-native microservices using tools like docker and kubernetes. Building end-to-end ai applications integrated into web, mobile, or api-first platforms. Managing ci/cd pipelines and observability for ai systems using tools such as github actions and mlflow. Implementing vector databases, retrieval-augmented generation (rag) pipelines, and orchestration tools like langchain and llamaindex. Building and integrating multi-agent frameworks (e.g., langgraph, langflow) to enable autonomous ai task execution. Translating complex business problems into software-engineered ai solutions aligned with best practices. Deploying on cloud platforms (aws, gcp, azure) and leveraging services such as sagemaker, vertex ai, or databricks. Proficiency in python and ml frameworks like pytorch, tensorflow, and hugging face transformers. Collaborating in cross-functional engineering environments including front-end (react, next.js) and platform teams. Familiarity with llm providers (openai, anthropic, meta, etc.) and working with chat/image-based model outputs. Hands-on experience with agent-based frameworks for intelligent orchestration. Additional experience or qualifications considered a plus: delivering ai applications using rag, vector databases, and agent-based frameworks. Working with multimodal inputs/outputs (text, image, audio). Fine-tuning models on domain-specific data. Applying responsible ai practices including governance, bias mitigation, and ethics. Ensuring consistency and quality in model outputs in production or regulated environments. Contributing to open-source projects or ai/ml publications. Full-stack development experience across front-end, back-end, and database layers. Seniority level: mid-senior level employment type: full-time job function: consulting, science, and information technology industries: it services and it consulting, operations consulting, and professional services referrals increase your chances of interviewing at pwc acceleration centers by 2x. #j-18808-ljbffr