Job Summary: We are seeking a results-driven Technical Project Manager with strong experience in managing AI-focused projects and tools. You will be responsible for overseeing cross-functional teams building AI/ML-driven products, platforms, or integrations—ensuring timely delivery, technical alignment, and strategic execution. The ideal candidate has hands-on familiarity with AI/ML workflows, prompt engineering, and tools like OpenAI, Hugging Face, LangChain, or vector databases. Key Responsibilities: Plan, execute, and manage AI-driven product or platform development using Agile methodologies. Translate business and product goals into structured AI projects with clearly defined scope and deliverables. Collaborate with data scientists, ML engineers, backend/frontend developers, and product stakeholders. Oversee model integration, API workflows, prompt optimization, and toolchain evaluation (e.g., LLMs, embeddings). Ensure scalability, performance, and ethical use of AI features in the product. Manage dependencies, risks, and cross-functional coordination. Drive the implementation of continuous delivery pipelines and AI ops. Monitor progress and communicate updates through clear reports and dashboards. Stay current with advancements in AI tooling and suggest improvements. Requirements: Bachelor’s or Master’s in Computer Science, Engineering, Data Science, or related field. 5+ years in technical project management, with 2+ years working on AI/ML-focused products or platforms. Strong understanding of AI/ML concepts, including LLMs, embeddings, prompt engineering, NLP, computer vision. Familiarity with tools like OpenAI, Hugging Face, LangChain, Pinecone, Weaviate, or vector databases. Experience with model deployment and AI infrastructure (e.g., FastAPI, Docker, cloud AI services). Skilled in using Jira, Trello, Notion, or similar project tools. Excellent leadership, communication, and cross-functional collaboration skills. Nice to Have: Experience managing AI chatbot or generative AI projects. Knowledge of ethical AI practices and responsible AI deployment. Certification in AI/ML or product management. Experience with RAG (Retrieval-Augmented Generation) architectures.
