While benefits may vary based on work location and the nature of the job, in general our employees have access to a 401(k)-retirement plan, disability coverage, an Employee Assistance Program (EAP), life insurance, health insurance, paid vacation and sick time, and paid holidays.
12-18 months
In this role, the nature of the work is dynamic and requires a collaborative attitude. While you have specific duties, it's important to understand that the entire team is responsible for the final delivery, and this may occasionally involve taking on additional tasks outside your primary responsibilities. The ability to adapt and contribute wherever needed is key to succeeding in this environment.
The team is seeking a hands on AI Agent Developer who can design, build, and iterate on data driven AI agents using technologies such as Microsoft Fabric, Azure, and Copilot Studio. The role requires strong engineering fundamentals, fast iteration, the ability to anticipate issues, and effective collaboration with both technical and non technical stakeholders.
AI Agent Development
• Build and deploy AI data agents connected to enterprise datasets and semantic models in Microsoft Fabric.
• Configure prompts, grounding strategies, exemplars, and agent instructions.
• Implement multi agent architectures, including parent/child routing, delegation, and fallback patterns.
Prompt Engineering & Evaluation
• Write clear system messages, input/output formats, and guardrails.
• Evaluate prompt behavior for reliability, correctness, retrieval quality, and output safety.
• Instrument evaluation loops and continuously improve models based on telemetry and feedback.
Data & Semantic Model Integration
• Integrate agents with Fabric Lakehouse/Warehouse datasets and semantic models.
• Work with data engineers to define data requirements and ensure proper schema alignment.
• Map user intents to the correct data fields and grounding sources.
Backend Engineering (Python / SQL / Azure)
• Build supporting utilities and APIs using Python, SQL, and Azure services.
• Integrate agents with retrieval layers such as Cognitive Search, vector indexes, or API endpoints.
Rapid Iteration & Quality
• Move quickly from MVP → v1 → vNext with minimal hand holding.
• Detect and diagnose issues such as data gaps, grounding mismatches, prompt failures, or routing errors.
• Recommend fixes and drive continuous improvements.
Collaboration & Communication
• Communicate technical reasoning clearly to engineers, architects, PMs, and non technical partners.
• Break work into clear phases, milestones, dependencies, and delivery plans.
Responsible AI Principles
• Apply widely recognized Responsible AI (RAI) practices such as safety, privacy, transparency, fairness, and accountability.
• Implement guardrails that reduce harmful or unintended model behavior.
• Recognize scenarios where model responses may pose risk and apply mitigation strategies.
Privacy & Data Protection
• Handle sensitive or private information using secure access patterns.
• Follow data minimization approaches when interacting with enterprise datasets.
• Ensure agents respect role based access, approved data sources, and avoid unnecessary logging or data exposure.
Governance & Process Alignment
• Document agent logic, prompts, and routing in an auditable way.
• Use appropriate environment and access controls.
• Follow standard engineering processes such as version control and change documentation.
• Participate in reviews related to data usage, security, and risk.
• Proven experience building AI agents, copilots, or conversational AI applications.
• Strong engineering skills in SQL, Python, and Azure services.
• Experience connecting agents to semantic models, BI datasets, or Fabric based data sources.
• Ability to design and operate multi agent systems (parent/child agents, routing logic, state handling).
• Strong problem solving skills and ability to iterate quickly with limited guidance.
• Clear communication skills across technical and non technical audiences.
• Experience with Copilot Studio, agent orchestration frameworks, or Fabric Data Agents.
• Familiarity with retrieval augmented generation (RAG), vector search, metadata enrichment, and evaluation pipelines.
• Understanding of enterprise data governance, privacy practices, and data stewardship.
• Experience creating telemetry dashboards or analytics to measure agent performance and quality.
To apply for this job email your details to resumes@biblioso.com