System Engineer 2, Full Stack Applied AI, AdTech

This is a New York City, NY, based position that works both in-office (2 days/week) and remotely. #LI-Hybrid

DIRECTV is seeking a System Engineer 2 with strong full stack software development and applied AI experience to build and deploy AI-powered products across our Advertising Technology ecosystem. This is a hands-on coding role with end-to-end responsibility for frontend experiences, backend services, APIs, AI integrations, data access, cloud deployment, and production support.

The ideal candidate is product-minded and forward deployed. This person works directly with business users, turns ambiguous needs into working software, prototypes quickly, and then hardens successful concepts into secure, reliable, maintainable applications that deliver measurable business outcomes. This is a software development position, not an infrastructure administration, data science, or machine-learning model development role.

Here’s what you’ll do:

Full Stack AI Product Development

• Design, code, test, deploy, and operate complete AI-enabled applications, including responsive user experiences, backend services, APIs, data access, and AI orchestration.
• Build intuitive conversational and workflow-based interfaces that help business users understand, refine, and act on AI-generated insights.
• Set up, configure, and extend AI cowork environments that allow business users to collaborate with AI agents, enterprise knowledge, approved tools, and shared workflow context.
• Own features end to end and produce maintainable, well-tested code suitable for enterprise production environments.
• Apply sound software design, accessibility, performance, security, and usability practices across the application stack.

Applied AI Engineering

• Build applications using LLMs, RAG, structured generation, tool calling, agents, semantic search, summarization, classification, and intelligent workflow automation.
• Design prompts, context assembly, model routing, validation, guardrails, fallbacks, and human review for reliable business use.
• Create evaluation datasets and automated tests for accuracy, groundedness, user value, safety, regression, latency, and cost.
• Select the simplest effective approach, including deterministic software or traditional analytics when an LLM is not appropriate.

Forward-Deployed Delivery

• Partner directly with Ad Sales, Operations, Product, Data, and Engineering teams to observe workflows and identify high-value opportunities.
• Translate incomplete requirements into prototypes, test them with users, and iterate rapidly based on evidence and feedback.
• Connect technical choices to outcomes such as productivity, decision speed, quality, revenue protection, or reduced operational effort.
• Support onboarding, adoption, documentation, training, and continuous improvement after launch.

Backend, Data & Enterprise Integration

• Develop scalable backend services using modern API, microservice, asynchronous processing, and event-driven patterns.
• Integrate applications with enterprise APIs, advertising platforms, Snowflake and other data stores, identity providers, content systems, and workflow tools.
• Build secure tool interfaces with clear contracts, authorization, validation, observability, and error handling.
• Implement caching, state management, retrieval, and data access patterns that improve quality, performance, and cost.

Production Engineering & Quality

• Implement CI/CD, infrastructure as code, automated testing, feature controls, monitoring, logging, tracing, alerting, and runbooks.
• Diagnose issues across browsers, frontend applications, APIs, models, retrieval, data, cloud services, and external integrations.
• Apply security, privacy, responsible AI, and data-governance requirements throughout design and delivery.
• Contribute reusable components, development standards, and engineering accelerators.

Here’s what you’ll need:

Experience & Education

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field.
• 5+ years of professional software engineering experience with substantial hands-on full stack development across frontend and backend systems.
• Proven experience delivering customer-facing or internal enterprise applications from concept through production operation.
• Practical experience integrating foundation models, agents, retrieval services, and intelligent automation into production software beyond isola…