22 days ago
Lewisville, TX, USAStaff+
Responsibilities
- Design and develop priority AI solutions, agents, copilots, RAG applications, workflow automations, AI-enabled applications, and reusable accelerators.
- Translate approved use cases and business requirements into solution designs, prototypes, technical plans, and implementation approaches.
- Create reusable code patterns, templates, reference implementations, agent frameworks, prompt and evaluation assets, APIs, and integration components.
- Partner with architecture, platform, governance, cybersecurity, data, technology, transformation, and business teams to deliver secure and responsible AI solutions.
- Guide engineers, analysts, citizen developers, and external delivery partners on AI engineering practices and solution quality.
- Support prototype-to-production transitions through testing, monitoring, reliability, deployment, documentation, supportability, and operational handoff.
- Assess technical feasibility, data readiness, integration needs, security implications, development complexity, maintainability, portability, and production readiness.
Requirements
- 10 or more years of progressive technology experience across hands-on software engineering, AI/ML engineering, data engineering, cloud-native application delivery, platform engineering, or intelligent automation.
- 5 or more years leading technical delivery of enterprise-grade software, AI/ML, GenAI, automation, data product, cloud application, or integration solutions from concept through production deployment.
- Demonstrated experience building AI-enabled applications such as agents, copilots, RAG solutions, LLM-powered workflows, APIs, decision-support tools, workflow automations, or ML-enabled products.
- Working knowledge of Azure AI, Azure AI Foundry, Azure OpenAI, Copilot Studio, Semantic Kernel, Power Platform, Fabric, Palantir Foundry, Palantir AIP, Palantir Ontology, Databricks, Power BI, vector search, RAG, embeddings, agent orchestration, governance controls, observability, evaluation, and MLOps/LLMOps.
- Strong command of solution architecture, secure API design, integration patterns, automated testing, cloud services, data access, identity and security, observability, reliability, and release management.
- Deep working knowledge of GenAI and AI engineering concepts including LLM behavior, prompt and context design, agent orchestration, retrieval, embeddings, evaluation, guardrails, responsible AI controls, observability, and human-in-the-loop patterns.
- Ability to translate ambiguous business opportunities into technical designs, prototypes, delivery plans, production-ready solutions, and reusable engineering patterns.
- Excellent communication and influencing skills across business stakeholders, engineers, architects, governance partners, vendors, and executive leaders.
Benefits
- The role includes a work environment involving computer-monitor use for more than 30% of the time and may require moderate physical effort, lifting materials or equipment weighing less than 15 pounds.
- Personal protective equipment may need to be worn, and reasonable accommodations may be made for individuals with disabilities.
Tech Stack
Databricks
Categories
