We require people to be on-site, 4 days/week at our Denver or NYC office and are unable to offer relocation support. Job Summary: LG Ads is seeking a motivated AI Platform Engineer to join our AI team and help build the in-house platform powering generative AI agents deployed business wide. You'll contribute to the end to end stack; LLM serving and inference, RAG pipelines, evaluation harnesses and the APIs and infrastructure that put agents in production driving efficiency, unlocking new revenue streams and enabling self-service data capabilities across the organization. The role is hands-on: you'll write production Python, integrate with services like AWS Bedrock and vector stores, instrument systems for observability and tune for latency, throughput and cost. We're looking for someone with a foundation in platform engineering and a working understanding of intent detection, query decomposition and context engineering, who is comfortable with agile delivery and can thrive in an ambiguous, fast-paced environment. Responsibilities: • Build and maintain LLM-powered services and APIs (FastAPI, webhooks, LangGraph), translating prototypes into production-ready endpoints with proper error handling, retries and timeouts. • Develop evaluation harnesses and offline/online eval pipelines to measure quality regressions, hallucination rates and task specific accuracy as models and prompts evolve. • Instrument services with logging, tracing, and metrics (latency percentiles, token usage, error rates) so production behavior is observable and debuggable. • Design and develop intelligent AI agents capable of intent recognition and decomposing complex queries into smaller, executable tasks that run in sequence or parallel. • Implement and optimize context engineering techniques to ensure agents leverage relevant short and long-term memory, as well as our aggregated knowledge base, for accurate and insightful responses. • Integrate AI agents with internal systems such as ACR, Mosaic, and Salesforce, and third-party services like SpringServe and DSPs. • Utilize and contribute to the development of standardized tooling protocols to streamline integration and maintenance of AI agents. • Collaborate with cross-functional teams, including product, and business units, to identify and build AI solutions that span the entire company. • Develop and implement solutions for operational efficiencies, such as automating media planning and integrating agents into Mosaic (Home Grown DSP). • Build client-facing tools for voice and natural language data queries, supporting custom data and contributing to data monetization efforts for the ACR platform. • Automate repetitive tasks in General & Administrative (G&A) functions, starting with Finance, and expanding to HR and IT Operations. • Enable self-service data access and analysis using AI agents, supporting diverse data sources. • Participate in agile development sprints, actively contributing to planning, execution, and review. • Manage ambiguity and adapt to evolving requirements in a rapidly developing AI landscape. Required Skills and Qualifications: • Proven experience in designing and developing Generative AI agents. • Strong expertise in intent detection and complex query decomposition. • Demonstrated experience with context engineering for AI models. • Proven understanding of knowledge graphs and/or vectorization as it relates to LLMs • Experience building RAG systems including low level design and implementation of such systems. • Solid understanding of large language models (LLMs) and their application in enterprise solutions, including foundational models like Llama 4 Maverick, Claude, and OpenAI. • Experience with cloud platforms, particularly AWS, for scalable compute and storage resources. • Familiarity with Databricks for processing structured and unstructured data, and its use as a runtime for agents and MCPs. • Experience working in an agile development environment. • Experience in Databricks / Snowflake and all the associated AI components • Experience in AWS ( or the two other big clouds) and the associated AI Services Education: • Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field. Application Deadline: July 7, 2026 Compensation & Benefits • Tier 1* (San Francisco Bay Area, New York City Tri-State Area, Los Angeles Metro Area, and Seattle Metro Area)$154,000 - $220,000/yr • Tier 2* (all other U.S. Locations outside of Tier 1)$135,000 - $192,500/yr • Offers Bonus • Benefits & Perks: 100% employer-paid medical, dental, and vision coverage for employees and eligible dependents. Company-paid life and AD&D, STD and LTD insurance, plus optional supplemental coverage. 401(k) with company match. Flexible Time Off (FTO). Paid parental leave. *Certain markets, including the San Francisco Bay Area, New York City Tri-State Area, Los Angeles Metro Area, and Seattle Metro Area, are aligned to Tier 1 compensation bands. All other U.S. locations are aligned to Tier 2 compensation bands. The compensation offered will take into account internal equity and may vary depending on the candidate's geographic region, job-related knowledge, skills, and experience.