Strategic Leadership & Team Management: o Lead, mentor, and develop a multidisciplinary team of software engineers and ML engineers, fostering a culture of excellence, collaboration, and continuous learning. o Define the strategic vision, technical roadmap, and key performance indicators (KPIs) for the GenAI Application Platform, ensuring alignment with overarching business objectives. o Manage resource allocation, project planning, and performance management to ensure timely and high-quality delivery of platform features.
Platform Development & Architecture: o Oversee the end-to-end lifecycle (design, development, deployment, and operation) of the platform's core components: Enterprise RAG: A scalable and secure service for grounding Large Language Models () on internal, proprietary data sources. [](data:,) Data Analytical Bot/Agent Framework: A conversational AI agent capable of querying structured and unstructured data to provide insights and analytics on demand via generative UI canvas. HyperAutomation Components: Reusable modules and APIs for creating complex, AI-driven workflows and automating business processes. o Champion best practices in software engineering, MLOps, system design, and security to ensure the platform is robust, scalable, and reliable. o Drive technical decision-making, evaluate new technologies, and manage the platform's technical debt.
Stakeholder Collaboration & Enablement: o Act as the primary technical partner and consultant for internal teams building on the GenAI platform. o Collaborate closely with engagement teams, business units, and other engineering leaders to understand requirements and translate them into platform capabilities. o Effectively communicate the platform's vision, capabilities, and roadmap to both technical and non-technical stakeholders. o Establish clear documentation, tutorials, and support channels to facilitate adoption and ensure a positive developer experience for platform users.
Main Requirements and Qualifications
Required Qualifications
Bachelor's or Master's degree in Computer Science, Engineering, Artificial Intelligence, or a related technical field.
8+ years of experience in software development, with a proven track record of shipping complex, scalable software products.
3+ years of experience in a direct management or technical leadership role, with demonstrated success in building and leading high-performing engineering teams.
Strong foundational knowledge of AI/ML, Natural Language Processing (NLP), and the modern AI technology stack (e.g., , transformers, vector databases).
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Experience with cloud computing platforms (e.g., AWS, GCP, Azure) and containerization technologies (e.g., Docker, Kubernetes).
Proficiency in Python and common data science/ML libraries (e.g., PyTorch, TensorFlow, Scikit-learn).
Preferred Qualifications
Direct, hands-on experience building or managing systems involving Retrieval-Augmented Generation (RAG), vector search (e.g., Pinecone, Milvus), and orchestration frameworks (e.g., LangChain, LlamaIndex).
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Experience developing conversational AI, chatbots, or data analysis tools.
Familiarity with HyperAutomation concepts, including Business Process Management (BPM) or Robotic Process Automation (RPA).
Proven ability to think strategically and execute methodically in a fast-paced, ambiguous environment.
Excellent verbal and written communication skills, with the ability to articulate complex technical concepts to diverse audiences.