System Engineer 2, Full Stack Applied AI, AdTech
About The Position
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 its Advertising Technology ecosystem. This is a hands-on software development role with end-to-end responsibility for frontend experiences, backend services, APIs, AI integrations, data access, cloud deployment, and production support. It is not an infrastructure administration, data science, or machine-learning model development role. The ideal candidate is product-minded and forward deployed, working directly with business users to clarify ambiguous needs, rapidly prototype working software, and evolve successful concepts into secure, reliable, maintainable production applications with measurable business outcomes. The role partners with Ad Sales, Operations, Product, Data, and Engineering teams to identify opportunities, build usable AI-enabled workflows, support adoption, and continuously improve products. The position is based in New York City and requires in-office attendance two days per week, as well as an in-person interview in New York City. Candidates outside the area must be willing and able to relocate at their own expense; company-paid relocation assistance is not available. The role may require approximately 10% travel. A background check may be required because the job involves routine access to DIRECTV and DIRECTV customer proprietary data.
Requirements
- Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field.
- At least 5 years of professional software engineering experience, including 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 isolated demos or notebooks.
- Strong experience with TypeScript or JavaScript and a modern UI framework such as React or Next.js.
- Experience building accessible, responsive applications with clear state management, component design, testing, and API integration.
- Ability to create polished business workflows, not only chat interfaces.
- Strong proficiency in Python and frameworks such as FastAPI.
- Experience designing REST or GraphQL APIs, service integrations, relational and NoSQL data stores, asynchronous processing, and distributed applications.
- Hands-on experience with cloud services, containers or serverless deployment, authentication and authorization, CI/CD, testing, and observability.
- Experience with foundation-model APIs or managed AI platforms and frameworks such as Bedrock, OpenAI, Anthropic, Snowflake Cortex, LangGraph, Semantic Kernel, or comparable technologies.
- Working knowledge of RAG, embeddings, vector search, tool calling, agents, context engineering, structured output, prompt management, evaluation, and guardrails.
- Proficiency using and setting up AI cowork environments for business users, including workspace configuration, role-based access, agent and tool integration, shared context, reusable workflows, and user onboarding.
- Ability to troubleshoot quality issues across prompts, context, tools, data, models, latency, and application behavior.
- Ability to work directly with business users, demonstrate frequently, receive feedback constructively, and turn learning into better software.
- Strong written and verbal communication skills, including the ability to explain decisions and tradeoffs clearly.
- High ownership, practical judgment, curiosity, and a bias toward delivering usable outcomes.
- Ability to meet the hybrid requirement of working in-office in New York City two days per week.
- Willingness and ability to relocate to the New York City area at the candidate's own expense if applying from outside the area.
Nice To Haves
- Experience in advertising, media, AdTech, MarTech, campaign operations, analytics, or other data-intensive business environments.
- Experience building workflow, analytics, decision-support, conversational BI, or operational automation products.
- Experience with AWS, Snowflake, Kubernetes, vector databases, feature flags, experimentation frameworks, and enterprise design systems.
- Experience contributing to shared platforms, component libraries, developer tooling, or reusable AI application patterns.
- A portfolio or concrete examples demonstrating ownership of frontend and backend production code.
- Experience with Node.js, Java, Go, or C#.
Responsibilities
- Design, code, test, deploy, and operate complete AI-enabled applications, including responsive user experiences, backend services, APIs, data access, and AI orchestration.
- Build 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 connect business users with AI agents, enterprise knowledge, approved tools, and shared workflow context.
- Own features end to end and deliver maintainable, well-tested code suitable for enterprise production environments.
- Apply software design, accessibility, performance, security, and usability practices across the application stack.
- 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.
- Choose the simplest effective approach, including deterministic software or traditional analytics when an LLM is not appropriate.
- 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 based on evidence and feedback.
- Connect technical decisions to outcomes such as productivity, decision speed, quality, revenue protection, or reduced operational effort.
- Support onboarding, adoption, documentation, training, and continuous improvement after launch.
- 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.
- 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.
Benefits
- The posting describes compensation as market-competitive and notes that total compensation includes salary, bonus, and benefits.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
