Gen AI Developer

• Strong production experience delivering Generative AI applications in enterprise or customer-facing environments.
• Hands-on expertise with Google Cloud Platform Vertex AI and Gemini models.
• Strong experience designing and implementing Retrieval-Augmented Generation (RAG) architectures.
• Experience building vector embedding and vector search pipelines.
• Strong cloud-native application development experience.
• Experience with serverless and container-based cloud solutions.
• Strong understanding of AI application architecture and deployment.
• Experience with DevOps, CI/CD, and MLOps practices.
• Strong communication and collaboration skills.
• Experience working in Agile software development environments.

Experience:

• 8+ years of experience in software development or engineering roles.
• Experience implementing enterprise-grade Generative AI applications in production environments.
• Hands-on experience with Vertex AI Studio and Google Cloud Platform AI services.
• Experience designing data grounding strategies for LLM-based applications.
• Experience building pipelines for preparing, processing, and embedding data.
• Experience with vector stores such as Vertex AI Vector Search.
• Experience with DevOps tools such as GitHub and Azure DevOps.
• Experience with CI/CD pipelines and MLOps implementation.
• Experience with LangChain or Agentic AI frameworks preferred.
• Experience with Model Context Protocol preferred.
• Experience integrating AI solutions with CRM, ERP, eCommerce, EMR, or EHR platforms preferred.
• Experience working with Agile methodologies and SDLC processes preferred.

Responsibilities:

• Design, develop, and implement scalable Generative AI solutions on Google Cloud Platform.
• Build and maintain Retrieval-Augmented Generation (RAG) systems for enterprise AI applications.
• Design and implement vector embedding and vector search pipelines.
• Develop data grounding strategies to improve response accuracy and contextual relevance.
• Implement AI applications using Vertex AI, Gemini, and related Google Cloud Platform services.
• Explore and implement Agentic AI concepts for autonomous AI workflows.
• Integrate Model Context Protocol capabilities for enhanced interoperability with external tools and systems.
• Collaborate with stakeholders, product owners, developers, and business teams to gather requirements and deliver AI solutions.
• Participate in proof-of-concept and proof-of-technology initiatives for new AI capabilities.
• Support Agile development practices and collaborate across engineering teams.
• Maintain and enhance AI application performance, scalability, and reliability.
• Contribute to CI/CD and MLOps processes for AI deployment and monitoring.
• Document technical designs, implementation details, and AI workflows.
• Adhere to organizational code of conduct and operational standards.

Should Have:

• Growth mindset and willingness to learn emerging AI technologies and frameworks.
• Strong analytical and problem-solving skills.
• Ability to communicate technical concepts clearly to technical and non-technical stakeholders.
• Strong collaboration and teamwork abilities.
• Ability to work independently in fast-paced enterprise environments.
• Strong attention to detail and quality-focused mindset.

Skills:

• Generative AI.
• Vertex AI.
• Gemini.
• Retrieval-Augmented Generation (RAG).
• Vector Embeddings.
• Vector Search.
• Google Cloud Platform (Google Cloud Platform).
• Vertex AI Studio.
• LangChain.
• Agentic AI.
• Model Context Protocol.
• MLOps.
• CI/CD.
• GitHub.
• Azure DevOps.
• Cloud-Native Development.
• Serverless Architecture.
• Container-Based Solutions.
• AI Application Development.
• Machine Learning Pipelines.
• API Integrations.
• Agile Methodology.
• DevOps.

Qualification and Education:

• Bachelor s degree in Computer Science or related field required.
• Equivalent combination of education and relevant experience may be considered.