AI Engineer or Architect

AI Engineer or Architect

LA, CA-Remote

Visa: Green CardGC-EADH1BH4-EADTN

Title -AI Engineer or Architect Contract Location-Los Angeles, CA-Remote Job Description : Job Requirements AI Developer/ Architect Role summary AI Developer will build and operate AI-enabled applications for customer experiences, employeeproductivity, and operations. Use cases may include conversational support, knowledge assistance,search and discovery, summarization, classification, decision support, workflow automation, andcontent/metadata operations.This is a production engineering role. Success requires strong software fundamentals, disciplinedevaluation, secure enterprise integration, and ownership of quality, latency, cost, observability, andsupportability throughout the application lifecycle.Key responsibilitiesAI application engineering• Build production applications using large language models, smaller task-specific models,retrieval-augmented generation, tool/function calling, workflow orchestration, anddeterministic business logic where appropriate.• Develop secure APIs, services, adapters, and event-driven integrations for digital channels,customer-care platforms, enterprise knowledge, billing and entitlement services,content/metadata systems, and internal workflows.• Implement authorization-aware tool use, input validation, idempotency, timeouts, retries,fallback behavior, circuit breakers, and human escalation paths.• Choose prompts, retrieval, rules, conventional machine learning, or fine-tuning based onevidence rather than defaulting every problem to a large model.Retrieval, data, and grounding• Build ingestion, chunking, metadata, indexing, retrieval, reranking, citation, freshness, anddeletion workflows for enterprise knowledge and approved content sources.• Preserve source permissions and customer/data boundaries throughout retrieval andgeneration; prevent unauthorized cross-user, cross-account, or cross-domain disclosure.• Partner with Data Engineering and domain owners on data quality, system-of-record alignment,lineage, and feedback loops.Evaluation and quality engineering• Create representative evaluation datasets and automated test suites for groundedness,relevance, correctness, task completion, refusal behavior, safety, robustness, latency, and cost.• Run regression testing across prompt, model, retrieval, tool, and policy changes; analyze failuremodes and improve the system using trace-based evidence.• Instrument online quality and business metrics, support controlled experiments, andincorporate human review for higher-risk or lower-confidence outcomes.Production operations and MLOps• Build CI/CD pipelines for code, configuration, prompts, evaluation assets, and model or indexchanges across separated development, test, and production environments.• Implement structured logging, tracing, token and infrastructure cost monitoring,model/provider health checks, alerting, dashboards, and operational runbooks.• Optimize throughput, latency, reliability, and cost using caching, batching, routing,prompt/context management, and appropriately sized models.• Participate in production support, incident response, root-cause analysis, and continuousimprovement.Security and responsible implementation• Implement controls for prompt injection, jailbreak attempts, unsafe tool use, data leakage,malicious content, model abuse, and dependency/supply-chain risk.• Apply DIRECTV requirements for PII and payment-card data, identity and access, secretsmanagement, retention, content rights, audit logging, and approved model/provider use.• Contribute reusable components to the AI control plane, including policy enforcement,prompt/model configuration, evaluation hooks, telemetry, and kill-switch or rollbackmechanisms.Team delivery• Work with Product Managers, UX, Solution Architects, AI Architects, Data Engineers,Cybersecurity, Quality Engineering, and Operations to deliver testable user outcomes.• Write maintainable code, automated tests, interface contracts, technical documentation,deployment guides, and operational runbooks; participate in code and design reviews.Required qualifications• Typically 10+ years in professional software engineering, including meaningful hands-onexperience delivering AI, machine-learning, search, NLP, or data-intensive applications toproduction; equivalent experience is welcome.• Hands-on experience with LLM APIs, prompt and context design, RAG, embedding/searchsystems, structured outputs, tool/function calling, and automated evaluation.• Experience with SQL and document/search stores, containers, CI/CD, source control, cloudservices, and observability practices.• Strong software engineering habits: modular design, automated testing, secure coding, peerreview, performance troubleshooting, and production ownership.• Ability to explain model limitations and engineering trade-offs to technical and nontechnicalpartners.• Bachelor's degree in computer science, engineering, data science, or a related field, orequivalent practical experience.Work Experience 5-7Years

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