AI Lead Engineer

AI Lead EngineerChicago, ILRate: $65/hr on C2CClient: UAL (United Airline)Job Description:The client is seeking dynamic and innovative AI Leads to drive our artificial intelligence initiatives. In this role, you will lead the development and implementation of AI solutions across various projects, guiding a team of data scientists and engineers. You will be responsible for identifying opportunities to leverage AI for business improvement, collaborating with cross-functional teams, and ensuring the successful deployment of AI models into production. Your leadership will help shape the AI strategy, enhance our technological capabilities, and deliver impactful solutions to our clients.Technical Stack:Retrieval-Augmented Generation (RAG) pipelines, semantic caching, and context window optimization.Function calling, tool use, and structured data extraction schemas.Evaluation metrics, tracing, and hallucination reduction guardrails.Designing agentic-first workflows and autonomous decision loops.Multi-agent coordination patterns (supervisor-worker, decentralized collaboration, stateful graphs).Frameworks like LangChain/LangGraph/Bedrock Core Runtime for state and memory management.Emerging interoperability standards like Model Context Protocol (MCP) and Agent-to-Agent (A2A) protocols and memory management.Vector databases (e.g., Milvus, Amazon Aurora PostgreSQL) for high-speed similarity search.Data pipelines and embedding generation workflows using Python, FastAPI, or Apache Spark.Cloud-native deployment on platforms like AWS (Amazon Bedrock, Lambda, EKS, SageMaker, S3, RDS, DocumentDB)Containerization and orchestration tools including Docker and Kubernetes.CI/CD pipelines for automated testing of non-deterministic AI outputs.Observability and logging pipelines for tracking agent token usage, latency, and failure states.Responsible AI frameworks, data privacy compliance, and bias mitigation guardrails.Roles & Responsibilities

Key Responsibilities

• Lead AI-related projects from conception to implementation, ensuring alignment with business goals.- Collaborate with product managers, engineers, and stakeholders to define project requirements and deliverables.- Oversee the data preparation process, including data collection, cleansing, and transformation.- Stay updated on emerging AI trends and technologies to integrate cutting-edge solutions.- Mentor and guide junior team members in AI best practices and methodologies.- Ensure high-quality deliverables by conducting rigorous testing and validation of AI models.- Communicate findings and insights to both technical and non-technical audiences.