Generative AI Engineer

A leading organization within the healthcare and pharmaceutical services industry is seeking an experienced AI Software Engineer Lead to design, build, and deploy production-grade artificial intelligence solutions. This position will focus on applied AI software engineering, including the integration of large language models, development of RAG and GraphRAG pipelines, creation of scalable AI inference services, and implementation of intelligent capabilities within data analytics and supply chain platforms.

Key Responsibilities

• Design and implement production-ready LLM-powered capabilities, including natural-language interfaces, intelligent summarization, anomaly explanations, and recommendation engines.
• Develop and optimize RAG and GraphRAG pipelines using structured, unstructured, vector, and knowledge-graph data sources.
• Build scalable AI inference services and APIs using Python and FastAPI.
• Integrate AI services with Databricks, PostgreSQL, Neo4j, Azure AI Search, Azure Event Hubs, Kafka, and other enterprise data platforms.
• Develop embedding pipelines, retrieval strategies, metadata frameworks, chunking approaches, and re-ranking solutions.
• Implement structured output validation, response grounding, hallucination controls, PII detection, content filtering, and responsible AI safeguards.
• Create automated evaluation pipelines to measure relevance, faithfulness, grounding accuracy, hallucination rates, latency, and cost.
• Productionize machine-learning models by implementing API services, input validation, output schemas, versioning, monitoring, and deployment controls.
• Build and deploy containerized services using Docker, Kubernetes, Helm, and CI/CD pipelines.
• Implement structured logging, distributed tracing, performance monitoring, token usage tracking, and cost-per-request controls.
• Support secure development practices and compliance requirements within regulated healthcare environments.
• Maintain technical documentation, model cards, audit trails, and validation records.
• Collaborate with data scientists, data engineers, software engineers, architects, product managers, security teams, and compliance stakeholders.
• Mentor other technical professionals on AI engineering and production deployment practices.
• Participate in Agile ceremonies and contribute to reusable AI components and engineering standards.

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related discipline.
• At least 8 years of hands-on software engineering experience.
• At least 3 years of experience focused on AI software development.
• Advanced proficiency in Python, FastAPI, async/await patterns, and Pydantic.
• Demonstrated experience integrating LLMs into production applications using Azure OpenAI, OpenAI APIs, Hugging Face, or similar technologies.
• Experience developing RAG pipelines, prompt frameworks, structured outputs, evaluation systems, and AI safety controls.
• Hands-on experience with Databricks, PySpark, Delta Lake, Databricks Workflows, and related AI capabilities.
• Experience with vector search platforms such as Azure AI Search, pgvector, or equivalent technologies.
• Experience with Neo4j or other graph databases and knowledge-graph-enabled AI solutions.
• Experience building and deploying REST APIs and containerized services using Docker and Kubernetes.
• Experience with CI/CD platforms such as GitHub Actions or Azure DevOps.
• Working knowledge of streaming technologies such as Azure Event Hubs or Kafka.
• Understanding of secure coding, data privacy, audit logging, and responsible AI practices.
• Strong communication skills and the ability to explain AI capabilities, limitations, costs, and risks to technical and business stakeholders.
• Full professional fluency in English, including speaking, writing, reading, and comprehension.

Preferred Qualifications

• Experience within healthcare, pharmaceutical services, supply chain, or another highly regulated industry.
• Knowledge of HIPAA, GxP, or 21 CFR Part 11 requirements.
• Experience with pharmaceutical supply chain processes, demand forecasting, order fulfillment, or healthcare analytics.
• Bilingual proficiency in English and Spanish.
• Microsoft Certified: Azure AI Engineer Associate.
• Microsoft Certified: Azure Developer Associate.
• Databricks or Apache Spark certification.
• Relevant LLM, AI engineering, or LLMOps certifications.

Ideal Candidate

The ideal candidate combines advanced AI expertise with strong back-end software engineering capabilities. This person has successfully transformed LLM and machine-learning capabilities into secure, observable, and scalable production services—not only research prototypes or notebooks.

Equal employment opportunities are provided to all qualified applicants without regard to any characteristic protected by applicable federal, state, or local law.