Senior Software Engineer - AI Core Engineering

Job Summary

We’re hiring a Senior AI Engineer to build the AI core capabilities and tooling that accelerate teams across Ad Technology. You will create shared agents, initialize rs, registries, and reusable services and web applications that make it fast, safe, and cost‑effective for engineering squads to adopt AI. Your work will emphasize common design principles, guardrails, governance, observability, and evaluation, so teams can deliver high‑quality AI solutions quickly—without reinventing the basics.

This role blends backend engineering, LLM orchestration, and developer enablement. You’ll design APIs, SDKs, reusable agents, and web‑based solutions that standardize adoption, define patterns for multi‑turn interactions, and provide evaluation/traceability so teams can confidently scale AI across Disney Ad Tech.

• AI Core Design & Principles:
  Define and implement shared design patterns for agents and services, including context management, retrieval, safety, and evaluation. Establish reusable blueprints that standardize how AI solutions are built across Ad Tech.
• Reusable Agents & Tools:
  Build production‑ready agents, initialize rs, and libraries for common use cases (summarization, troubleshooting, semantic extraction). Develop high‑quality APIs and SDKs that simplify adoption of AI capabilities by other engineering teams.
• Shared Services & Web Applications:
  Deliver core services for retrieval, memory, and orchestration, integrated with enterprise and consumer‑facing systems. Create internal webapps and dashboards that expose AI capabilities, evaluation metrics, and adoption accelerators.
• Safety, Governance & Observability:
  Embed guardrails, compliance checks, and prompt safety into all shared components. Implement model evaluation and observability frameworks for quality, reliability, and cost monitoring at scale.

• 5+ years of backend or applied AI/ML engineering with a track record of building production‑grade systems.
• Proficiency in Python (libraries, testing, packaging) and building scalable APIs or SDKs.
• Hands‑on experience with LLM APIs (e.g., OpenAI, Anthropic, Claude) and frameworks such as Lang Chain or Lang Graph.
• Experience integrating with enterprise AI services such as AWS Bedrock or Azure AI Foundry, including model invocation, routing, and governance integration.
• Experience developing reusable agents, libraries, or internal tooling adopted by multiple teams.
• Knowledge of guardrails and evaluation techniques for LLMs, including prompt safety, output validation, and quality regression testing.
• Strong collaboration and communication skills; able to work across infra, data, security, and product teams.

• Experience building AI enablement tooling (registries, agent initialize rs, internal frameworks) for enterprise use.
• Familiarity with observability for AI systems: tracing, latency and cost dashboards, drift detection.
• Knowledge of AI gateway patterns (e.g., routing, usage throttling, model fallback, quota enforcement).
• Exposure to multi‑agent orchestration, simulation frameworks, or synthetic data for testing/evaluation.
• Understanding of enterprise governance: security, compliance, audit, and policy enforcement in AI systems.
• Previous experience in a developer enablement role (platform engineering, frameworks, SDKs) where reusable components accelerated adoption across large organizations.

Bachelor’s degree in Computer Science, Engineering, or related technical field (Master’s preferred), or equivalent experience.

The hiring range for this position in Los Angeles, California is $141,900 to $190,300 per year, Seattle, WA is $148,700 to $199,400, and San Francisco, CA is $155,400 to $208,400 per year. The base pay actually offered will take into account internal equity and also may vary depending on the candidate’s geographic region, job‑related knowledge, skills, and experience among other factors.

A bonus and/or long‑term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial, and/or other benefits, dependent on the level and position offered.