Lead Engineer (Python/Java, React, Kubernets, GKE)

Job Description

Overview Join the Prodapt team in building a unified, enterprise-grade environment for developing, deploying, and scaling generative AI (GenAI) applications and agentic workflows. You will help design, develop, and optimize robust GenAI solutions that empower teams to leverage LLMs, agent frameworks, and retrieval-augmented generation (RAG) for a wide range of business and technology use cases. Responsibilities Design, develop, and maintain GenAI applications and agentic workflows using unified LLM developer APIs and Agent Builder. Integrate and manage foundation and tuned LLMs (e.g., Gemini, GPT, Llama, Claude) for both internal and external use cases. Build and optimize RAG pipelines leveraging centralized vector databases and embedding stores. Develop and deploy GenAI models and BYOA (Bring Your Own Application) solutions as Docker images on Kubernetes-based infrastructure. Implement prompt engineering, orchestration, and evaluation workflows using workbench plugins and browser extensions. Support and extend user interfaces (web UI, browser extension, Slack integration) for interacting with GenAI agents and tools. Ensure robust security, compliance, and governance, including role-based access control, audit logging, and data privacy controls. Collaborate with data scientists, ML engineers, and product teams to deliver scalable, production-grade GenAI solutions. Participate in code reviews, architecture discussions, and continuous improvement of the GenAI platform. Requirements Required Technical Skills Proficiency in Python and experience with LLM/GenAI model development and integration. Experience with containerization (Docker) and orchestration (Kubernetes) for deploying GenAI applications. Familiarity with LLM APIs (AI, OpenAI, Gemini, etc.) and prompt engineering best practices. Hands-on experience with vector databases, RAG workflows, and embedding management. Experience with web UI development (React, Next.js, or similar frameworks) and API integration. Strong understanding of security, governance, and compliance in AI/ML environments. Experience with CI/CD tools and automation for GenAI workflows. Excellent troubleshooting, debugging, and communication skills. Preferred Qualifications Experience with agentic frameworks (LangChain, CrewAI) and multi-agent orchestration. Familiarity with large-scale financial/ML platforms. Exposure to GenAI evaluation frameworks (LLM_EVAL, AGENT_EVAL) and monitoring tools. Experience with Slack bot development, browser extension integration, or desktop app development. Knowledge of data privacy, vulnerability scanning, and compliance automation.