About the Role:

Azurity is seeking an Agentic AI Developer to design, build, and deploy AI agents and multi-step autonomous workflows that integrate with internal systems and business processes.

Key Responsibilities:

• Design and build AI agents that use large language models to plan, reason, and execute multi-step tasks, including data retrieval, document generation, and cross-system workflows
• Integrate agents with internal and third-party systems via APIs, MCP servers, and other tool-calling frameworks
• Build and maintain orchestration layers for multi-agent workflows, including error handling, retries, and human-in-the-lead checkpoints

Required Skills and Experience:

• Three or more years of professional software development experience, including at least one year working directly with large language models or agentic AI systems
• Strong proficiency in Python or a similar language, with experience using large language model APIs such as Anthropic, OpenAI, or comparable providers
• Hands-on experience building tool-calling or function-calling agents, including designing tool schemas and managing multi-turn reasoning
• Familiarity with agent orchestration frameworks and concepts (ReAct, planning/reflection loops, multi-agent coordination)
• Experience with retrieval-augmented generation (RAG), vector databases, and embedding models
• Solid understanding of API design, integration patterns, and asynchronous systems
• Experience implementing evaluation, observability, and safety guardrails for AI systems in production
• Comfort working in a regulated industry, with attention to data privacy, security, and compliance requirements
• Strong communication skills, with the ability to translate business problems into technical solutions and explain AI system behavior to non-technical stakeholders

Preferred Qualifications:

• Experience in pharmaceutical, healthcare, or other regulated industries
• Familiarity with Model Context Protocol (MCP) or similar tool-integration standards
• Experience with enterprise systems commonly used in pharmaceutical environments, such as Veeva, Salesforce, ERP, or IT service management platforms
• Background in prompt engineering and fine-tuning/evaluation of LLMs
• Exposure to cloud platforms (AWS, Azure, or GCP) and MLOps practices.