Lead AI Engineer (Digital Marketing sphere)

Company Background Our client is a global technology company transforming the way brands and agencies make marketing decisions. Its platform enables marketers to plan and activate cross-channel, programmatic media campaigns using real-time research, proprietary audience data, advanced analytics, and more than 150 integrated partners including Facebook, Instagram, Pinterest, Snapchat, and Twitter. The company operates across North America, Europe, the Middle East, Asia, and Australia. Project Description The project focuses on developing AI-driven solutions for advertising campaign analytics, insights, and automation. The Lead AI Engineer will provide technical leadership across two GenAI teams working on conversational agents and platform capabilities. Technologies Python, FastAPI, SQLAlchemy, Pydantic TypeScript, NestJS REST APIs, SSE, WebSockets Core LLM concepts, prompt engineering, reasoning strategies, RAG, structured outputs, tool calling Agentic and graph-based workflows, multi-agent orchestration SQL, relational databases, PostgreSQL, data modeling Microservices, API routing, caching pytest, Jest, LLM evaluation tests What You'll Do Lead and mentor two GenAI teams developing conversational agents, manage team roadmaps, foster team collaboration, and oversee project delivery; Develop and implement innovative AI-driven solutions to advance platform capabilities; Collaborate with stakeholders, including developers, product managers, and business operations teams, to align goals and deliverables; Lead the development of conversational agents from concept through production deployment; Research advanced AI technologies and integrate external APIs and services into AI-driven solutions; Job Requirements Bachelor’s degree in Computer Science or a related field; 3+ years of experience leading engineering teams; 6+ years of experience building customer-facing full-stack applications; 2+ years of hands-on experience with Python, including FastAPI, asynchronous programming, SQLAlchemy ORM, and Pydantic; Experience with TypeScript and NestJS; Experience designing and implementing AI agents using LangGraph and/or LangChain, including graph-based workflows, tool calling, structured outputs, and checkpointing; Strong understanding of LLM concepts and AI engineering practices, including RAG, prompt engineering, LLM parameters, guardrails, observability, and tracing; Understanding of machine learning concepts, including models, model validation, and feature engineering; Experience designing REST APIs and implementing streaming responses using SSE and/or WebSockets; Experience working with SQL and NoSQL databases, including relational databases such as PostgreSQL; Experience with automated testing using pytest, Jest, and/or evaluation tests for AI systems; Familiarity with distributed system design, microservices, caching, API routing, and multi-agent orchestration; Proactive and collaborative…