Artificial Intelligence Jobs in Richardson, TX

Lead a forward‑deployed AI solutions team to translate enterprise AI capabilities into business outcomes. Partner with executives to co‑design and deliver priority use cases, drive AI productivity tool adoption, establish repeatable AI solution patterns, and feed learnings back into the AI platform and governance. Balance rapid delivery with enterprise rigor while coaching teams and managing stakeholders.

Design, build, and deploy production-ready AI solutions across enterprise platforms. Implement LLM workflows (prompt engineering, embeddings, RAG), integrate with enterprise data and SaaS systems, ensure operational readiness (monitoring, logging, performance), and partner with Security, Privacy, IT, and business teams to meet governance and compliance requirements.

Lead design and implementation of agentic AI/ML solutions and modern software (APIs, microservices, CI/CD, streaming) on cloud platforms. Bridge legacy IBMi AS400 systems with modern AI, train and fine-tune models, oversee lifecycle, mentor engineers, set technical direction, and improve automation and testing across claims adjudication systems.

Lead design and implementation of enterprise-scale agentic AI and cloud-native solutions (APIs, microservices, CI/CD, streaming). Architect RAG, vector DBs, MCP integrations and multi-agent orchestration, mentor engineers, drive technical standards, research emerging technologies, and partner across teams to deliver scalable, secure AI solutions for claims adjudication.

Lead go-to-market strategy for Tanium Atlas and AI-powered automation and governance within the Autonomous IT platform. Define positioning and messaging, engage customers and market to inform product direction, create high-impact content and sales enablement, drive launches and competitive intelligence, and collaborate cross-functionally to increase awareness and adoption.

The Senior AI Cloud Architect will design and deliver AI/LLM-powered cloud applications, lead architectural decisions, and ensure production readiness with a strong focus on scalable solutions.

Design, build, test, and maintain scalable Java backend services while developing AI-driven engineering workflows and agentic tooling. Own CI/TDD practices, create automated tests, integrate AI tools and prompts into development pipelines, collaborate on architecture and Agile ceremonies, mentor peers, and evaluate emerging AI technologies to improve engineering velocity and quality.

Design, implement, and support scalable Java-based Workforce Management services. Own features end-to-end, drive architectural decisions, mentor engineers, and integrate AI-assisted development tools and workflows to improve engineering productivity and quality.

Build infrastructure automation and AI-driven operations for a global multi-region cloud platform. Design end-to-end provisioning pipelines, integrate AI agents for incident intelligence and change-risk scoring, and collaborate with SRE/DevOps to translate manual workflows into secure, compliant automation across sovereign regions.

Lead architecture and development of scalable Java-based WFM server-side solutions, champion AI-assisted development, drive engineering standards, mentor senior engineers, resolve production issues, and collaborate cross-functionally to deliver enterprise software.

Owner of quality for an LLM-based multi-agent claims adjudication pipeline. Build evaluation frameworks, automated LLM-grading workflows, function-call and reasoning-trace auditing using Vertex AI. Integrate CI/CD regression, Auto-SxS comparisons, and large-scale mocking to ensure compliance and accurate adjudications for DOL/DOI audits.

Lead design and implementation of agentic AI systems for claims adjudication using Gemini and Vertex AI. Build production-grade Python agents, implement RAG, grounding, stateful orchestration with human review, input/output guardrails, and Google Cloud DLP integration. Drive backend patterns, optimize model behaviors, and supervise fine-tuning to ensure reliable, auditable outputs in healthcare claims workflows.

Lead design and delivery of scalable, production-grade agentic AI and automation systems integrated with enterprise collaboration tools (Slack, Outlook, Zoom, SharePoint, Copilot). Drive architecture-to-execution, CI/CD, infrastructure-as-code, monitoring, and cross-team collaboration to scale AI-driven workflows and improve associate productivity.

The Principal Engineer will lead the design and development of technical solutions, oversee project teams, and maintain existing solutions, focusing on APIs and innovative technology applications.

Design, develop, test, deploy, maintain, and enhance large-scale software solutions. Provide technical leadership and manage project priorities. Fine-tune foundation models and build adapters (Llama Factory, PEFT). Apply RAG techniques to populate and query vector databases (Weaviate). Build custom applications using LLM frameworks such as LangChain and DSPy.

On-site senior engineer and client-facing technical lead responsible for designing and delivering LLM-powered features (RAG, agentic architectures), integrating OpenAI/Anthropic/Azure OpenAI, writing production full‑stack code, coordinating offshore teams, owning delivery end-to-end, and representing ISHIR in executive stakeholder meetings.

Lead architecture and development of a scalable, real-time Platform Chat product using LLMs and agent frameworks. Build orchestration layers, workflow automation, LLM integrations, and systems for observability, safety, and performance while mentoring engineers and collaborating with product and data science teams.

Lead and scale a Data & AI Support Engineering team to resolve complex Spark, streaming, Lakehouse, and Databricks issues. Build AI-enabled support workflows, automations, and runbooks; partner with Engineering/Product to operationalize diagnostics and observability; manage KPIs, escalations, hiring, training, and on-call incident response while acting as a technical escalation leader for enterprise customers.