We are looking for GenAI Solution Designer and Developer for our client in Dallas, TX.
Job Title: GenAI Solution Designer and Developer
Job Location: Dallas, TX
Job Type: Contract
Job Overview:
Requirement/Must Have:
- 1+ years of GenAI Solution Design & Development experience.
- Experience in designing and building LLM-powered applications using RAG, embeddings, and vector search architectures.
- Experience in developing Copilot-based AI assistants and agents for enterprise use cases such as automation, Q&A, and workflow orchestration.
- Experience in engineering end-to-end GenAI pipelines including prompt engineering, context handling, and response orchestration.
- Experience in building reusable AI components (agents, pipelines, guardrails) to accelerate solution delivery.
- Experience in developing and customizing copilots using Microsoft Copilot Studio / Azure Foundry.
- Experience in integrating copilots with enterprise systems (ERP, CRM, ServiceNow, APIs).
- Experience in designing conversational workflows, triggers, and automation actions.
- Experience in enabling enterprise-grade features such as role-based access and identity integration.
- Experience in knowledge grounding using enterprise data.
- Experience in implementing responsible AI guardrails (toxicity, hallucination control).
- Experience in developing AI-powered applications using Snowflake Cortex AI functions and Snowpark.
- Experience in implementing vector search, semantic models, and AI-driven analytics workflows.
- Experience in integrating structured and unstructured data pipelines to support AI models.
- Experience in building self-service AI capabilities on data platforms with governance and cost optimization.
- Experience in building and deploying models using Azure OpenAI, AWS Bedrock, or similar platforms.
- Experience in creating scalable pipelines for model deployment, monitoring and observability, and continuous improvement loops.
Responsibilities:
- Design and build LLM-powered applications using RAG, embeddings, and vector search architectures.
- Develop Copilot-based AI assistants and agents for enterprise use cases.
- Engineer end-to-end GenAI pipelines including prompt engineering, context handling, and response orchestration.
- Build reusable AI components to accelerate solution delivery.
- Develop and customize copilots using Microsoft Copilot Studio / Azure Foundry.
- Integrate copilots with enterprise systems.
- Design conversational workflows, triggers, and automation actions.
- Enable enterprise-grade features such as role-based access and identity integration.
- Implement responsible AI guardrails.
- Develop AI-powered applications using Snowflake Cortex AI functions and Snowpark.
- Implement vector search, semantic models, and AI-driven analytics workflows.
- Integrate structured and unstructured data pipelines to support AI models.
- Build self-service AI capabilities on data platforms.
- Build and deploy models using Azure OpenAI, AWS Bedrock, or similar platforms.
- Create scalable pipelines for model deployment, monitoring, and observability.
Nice to Have:
- Implement AI guardrails, evaluation frameworks, and feedback loops for production systems.
- Leverage tools like GitHub Copilot for code generation, test automation, debugging, and documentation.
- Automate SDLC activities using GenAI.
- Enable developer productivity improvements and automation-first engineering.
- Align business priorities with AI outcomes.
- Define and curate strategy for model training, inference, and monitoring.
- Integrate GenAI into enterprise workflows.
Skills:
- Hands-on knowledge of data models, SQL, and data lifecycle management.
- Strong knowledge of AI/ML algorithms, data structures, and performance optimization.
- Proficiency in programming languages such as Python, SQL, and PySpark.
- Experience with cloud platforms (AWS, Azure) and big data technologies (Spark, Snowflake).