Job Title : Lead GenAI
Location : Remote.
Job Description: Lead GenAI Developer (Google Cloud Platform / Vertex AI / Gemini)
Role Overview
The Lead GenAI Developer will be responsible for architecting, designing, and guiding the delivery of GenAI solutions on Google Cloud Platform for a healthcare payer client. This role involves leading technical design, driving development best practices, reviewing solution architectures, and mentoring a team of developers. The ideal candidate has deep hands on experience with Vertex AI, Gemini models, GenAI SDKs, and building scalable enterprise-grade AI solutions within regulated environments.
Key Responsibilities
Lead the end-to-end design and development of GenAI solutions using Google Cloud Platform services, Vertex AI, Gemini, and related GenAI tools.
Own solution architecture, model integration patterns, and technical strategy for AI initiatives.
Work closely with client stakeholders, data science teams, and cloud engineering teams to translate requirements into scalable GenAI implementations.
Provide technical leadership and mentorship to AI developers and engineers on the team.
Build, fine-tune, evaluate, and deploy LLMs and multimodal models using Vertex AI and Gemini APIs.
Develop secure, compliant data and model pipelines adhering to healthcare payer regulatory requirements (HIPAA, PHI/PII protection).
Optimize model performance, cost, scalability, and reliability.
Review and enhance prompt engineering strategies, RAG pipelines, and model orchestration workflows.
Ensure code quality, automation, CI/CD integration, and operational excellence for GenAI services.
Stay current on Google Cloud AI advances and guide their adoption.
Required Skills & Experience
7+ years of software development experience, with at least 3+ years in AI/ML or GenAI development.
Strong hands-on experience with Google Cloud Platform, especially Vertex AI, BigQuery, Cloud Storage, Cloud Functions, and Cloud Run.
Expertise with Gemini models, Vertex AI Model Garden, and GenAI SDKs.
Proven experience designing and deploying RAG (Retrieval-Augmented Generation) or similar hybrid architectures.
Proficiency in Python, REST API development, and containerized workloads.
Experience leading technical teams and overseeing end-to-end solution delivery.
Familiarity with healthcare payer domain data (claims, prior auth, clinical data) is preferred.
Strong understanding of data governance, model security, and compliance requirements for healthcare.