Applied AI Engineer

Job Description

Job Description

Job Title: AI Engineer Location-Type: Conshohocken, PA  Start Date: July 2026 Duration: 6 months Compensation Range: $75-80/hr  Benefits: Eligible for Health, Dental, Vision, and 401K Visa Sponsorship: Not eligible for visa sponsorship Job Description: The client is seeking an AI Engineer to design, build, and deploy LLM-based solutions, autonomous agents, and AI orchestration workflows that enhance how the organization consumes data and reporting insights. Job Summary •Integrate AI-generated insights, narratives, and analysis into existing Power BI reports and dashboards. •Build domain-specific AI agents that support internal teams, including automating first-pass analysis of service tickets. •Implement agent memory, context management, RAG retrieval strategies, and orchestration patterns to support scalable AI architecture. •Design and deploy reusable AI components, skills, and agent frameworks that can be leveraged across multiple teams. •Contribute to the design and deployment of Model Context Protocol (MCP) servers and integrations to expose enterprise data to AI systems. •Maintain and evolve the existing Power BI report portfolio, including semantic models, DAX measures, and Power Query transformations. •Ensure AI integrations comply with enterprise data governance, privacy, security, and access control standards. Minimum Requirements: •2 years of hands-on production AI engineering experience, including building LLM applications and AI agents. •Proven experience with RAG architectures, agent frameworks, prompt orchestration, and token optimization. •Strong Python and SQL skills with demonstrated ability to design scalable, reusable AI architecture. •Proven Power BI development experience, including semantic modeling, DAX, and Power Query. •Ability to work autonomously, manage a mixed AI/BI backlog, and communicate clearly with non-technical stakeholders. Preferred Qualifications: •Experience with ServiceNow or other enterprise platforms such as Salesforce or Dynamics 365, and system integration patterns. •Experience implementing AI governance, guardrails, and responsible-AI practices including monitoring and evaluation. •Experience reducing LLM costs and token usage at scale. •Familiarity with the Microsoft data platform, including Fabric, Synapse, and Purview. •Experience embedding AI-generated narratives or insights directly into BI reporting tools. •Experience building AI frameworks adopted across multiple business teams.