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Were looking for a Lead Software Engineer to help shape the future of Ad Technology's Generative AI platform, with a focus on building reusable capabilities and intelligent agents that streamline and automate critical operational workflows. This is a unique opportunity to apply cutting-edge AI tools to real-world challenges, improve efficiency, reduce manual effort, and empower teams across our ad delivery ecosystem. You'll play a dual role: Engineering reusable GenAI platform services, such as prompt routing, vector search, auditing, guardrails, and secure gateway abstraction Building production-ready agents using frameworks like LangGraph and LangChain to automate workflows across infrastructure, support, CI/CD, and business operations This role is ideal for engineers excited to work at the intersection of backend systems, AI orchestration, platform architecture, and enterprise automation. You'll be joining a collaborative team at the forefront of GenAI enablement, helping to shape how modern AI tools are applied to real operational challenges in one of the most advanced ad tech environments. Responsibilities: Design and build reusable GenAI platform components, including prompt orchestration layers, secure gateway abstraction using tools like LiteLLM, Portkey, or Kong, embedding and retrieval infrastructure using vector databases like Pinecone or FAISS, audit, logging, and trace analysis with tools like LangSmith, and guardrails integration for output validation, safety checks, and policy enforcement. Develop multi-turn LLM agents and tools using LangGraph and LangChain to automate operational workflows. Build robust APIs, SDKs, and accelerator components that serve as initializers for internal product teams, bots, and platforms to rapidly integrate and adopt GenAI services. Standardize approaches to context management, tool calling, fallback handling, and observability across agents. Ensure platform components meet security, governance, and compliance standards. Partner with infrastructure, data, security, and product teams to integrate GenAI workflows into existing systems. We are committed to creating inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity employer that believes everyone matters. Qualified candidates will receive consideration without regard to race, religion, sex, age, marital status, national origin, sexual orientation, citizenship status, disability, or any other protected characteristic. If you need assistance or a reasonable accommodation due to a disability during the application process, please contact Human Resources. The EEOC "Know Your Rights" Poster is available here. To learn more about how we handle your private information, review Insight Global's Workforce Privacy Policy: . Qualifications: 8+ years of backend or platform engineering experience, with a track record of building scalable APIs Hands-on experience integrating with LLM APIs such as OpenAI, Claude, and Anthropic, and building LLM-powered workflows, agents, or AI assistants Proficient in Python; familiarity with LangChain, LangGraph, or similar frameworks Knowledge of observability practices for LLM systems, including logging, latency tracking, and output monitoring Experience with LLM evaluation and testing frameworks to validate prompt behavior and agent reliability Strong understanding of cloud-native design, secure API integration, and scalability Experience with vector databases like Pinecone, FAISS, or Weaviate, and retrieval-augmented generation techniques Ability to build modular, reusable GenAI components for cross-functional adoption Comfort with CI/CD pipelines and collaborating with DevOps teams Nice to Have Skills & Experience Experience with LangSmith, PromptLayer, or tracing tools for debugging LLM workflows Knowledge of AI gateway patterns and usage throttling tools like Kong, LiteLLM, or Portkey.ai Familiarity with guardrails, safety evals, prompt injection defense, and model governance Experience building platforms or enablement tooling for multiple engineering teams Exposure to infrastructure or DevOps automation is a plus Benefits include medical, dental, vision insurance, HSA, FSA, DCFSA accounts, 401k with employer matching, paid sick leave, and other paid time off as per law. #J-18808-Ljbffr