Jobs at KANINI

Owns product value, viability, vision, strategy, roadmap, KPIs, and ROI for moderately complex AI-enabled products. Leads cross-functional teams, conducts user and market research, guides experimentation, and aligns product outcomes with business objectives. Uses agentic AI tools for research, prototyping, analysis, specification, testing, and compliance while establishing safeguards for hallucination, bias, drift, and responsible deployment.

Leads hands-on development of applied AI and software engineering solutions across architecture, coding, testing, deployment, and support. Designs GenAI applications, integrates LLMs, builds RAG pipelines, and applies agentic AI practices throughout the software lifecycle. Maintains technical standards, reviews code, mentors engineers, collaborates with product and customer teams, and delivers scalable cloud-native solutions using rapid experimentation and automated quality practices.

Own Salesforce architecture, roadmap, governance, integrations, security architecture, DevOps, and the migration to Revenue Cloud. Lead internal administrators and external partners, oversee platform reliability, manage capacity and delivery standards, and partner with executives across business functions. The role requires hands-on Salesforce CPQ and Revenue Cloud expertise, complex integration architecture, acquisition onboarding, team leadership, and strong stakeholder communication.

Develop and maintain advanced iOS applications and scalable Node.js APIs for healthcare environments. Integrate REST, GraphQL, third-party services, and event-driven systems while supporting offline synchronization with NoSQL databases. Manage containerized deployments and cloud infrastructure using Docker, Kubernetes, GCP, and Anthos. Ensure HIPAA-compliant data handling, secure authentication, observability, performance, testing, and maintainability. Collaborate cross-functionally, contribute to architecture decisions, troubleshoot applications, and mentor junior developers.

Design, develop, and optimize scalable batch and real-time data pipelines on GCP. Implement Medallion Architecture, build Python and PySpark transformations, optimize BigQuery and SQL workloads, deploy Dataflow pipelines, and orchestrate workflows with Cloud Composer and Airflow. Manage GCS storage, CI/CD, version control, IAM, data governance, security, reliability, scalability, and cost efficiency across enterprise data platforms.

Define and govern enterprise data architecture, integration frameworks, data models, governance standards, and scalable GCP data platforms. Lead architecture decisions covering batch and real-time processing, Data Mesh and Lakehouse patterns, ETL/ELT, APIs, streaming, security, performance, observability, privacy, and compliance. Partner with technical and business stakeholders, guide data initiatives, establish platform standards, and mentor engineering teams on architecture and integration best practices.

Build and deploy full-stack, backend-heavy applications and scalable Java services on GCP. Develop AI-powered solutions using Vertex AI and agentic AI frameworks, owning development, testing, deployment, and production support. Collaborate with clients and cross-functional stakeholders in ambiguous, forward-deployed environments, rapidly prototyping solutions, troubleshooting issues, and iterating based on user feedback.