? Role Overview We are looking for an experienced Generative AI Architect with strong Python expertise to lead the design, development, and architecture of end-to-end GenAI systems. You will work closely with cross-functional teams (product, data science, backend, infrastructure) to translate business requirements into scalable, efficient, production-grade AI/ML solutions. You will also mentor engineers, define best practices, and ensure robust, secure, maintainable architectures. Key Responsibilities Lead the architecture, design, and deployment of Generative AI solutions (LLMs, RAG, fine-tuning, embedding pipelines, etc.). Define AI / GenAI system components: prompt engineering, model selection, agent frameworks, orchestration, inference, and post-processing. Design data pipelines and storage architectures for ingestion, preprocessing, embedding, and retrieval. Select and integrate vector databases, knowledge sources, document stores, etc. for semantic search / retrieval. Ensure scalability, performance, security, reliability, and cost-efficiency of AI systems. Build or oversee robust MLOps and LLMOps pipelines (training, evaluation, deployment, monitoring, versioning). Drive proof of concepts (PoCs), prototypes, and pilot projects for new GenAI features / capabilities. Collaborate with product and business stakeholders to define use cases, metrics, and translate requirements. Mentor, guide, and review work of engineers, ML engineers, and data engineers; enforce best practices and architectural standards. Stay current with latest GenAI technologies, frameworks, and models. Evaluate new tools and frameworks, recommend what is appropriate. Ensure compliance with ethical AI usage, privacy, data governance, and model safety guardrails. Required Skills & Qualifications Bachelor?s / Master?s in Computer Science, AI/ML, or related field (or equivalent practical experience). Experience: ~8?15 years in software engineering, including 3?5+ years in AI / Generative AI architecture / leadership roles. Strong proficiency in Python, including AI/ML libraries and frameworks (e.g., PyTorch, TensorFlow, Hugging Face, etc.). Deep understanding of large language models (LLMs), embeddings, vector search, RAG pipelines, prompt engineering, MCP (Model Context Protocol). Experience with GenAI frameworks / tools (e.g., LangChain, LlamaIndex, Haystack). Familiarity with agentic AI, multi-agent orchestration, or relevant frameworks. Strong knowledge of cloud platforms (AWS, Azure, GCP) and cloud-based AI/ML/GenAI services. Experience with containerization and orchestration (Docker, Kubernetes) and infrastructure as code. Strong software architecture skills: microservices, REST/API design, data storage & retrieval, scalability, high availability. Good understanding of DevOps/MLOps, version control, and CI/CD pipelines. Excellent problem-solving, analytical thinking, and communication skills; ability to explain technical ideas to non-technical stakeholders. Experience mentoring / leading teams with strong decision-making and technical trade-off evaluation capabilities. Knowledge of ethical AI practices, data privacy, security, and model governance. Preferred / ?Nice to Have? Experience in Cyber Security domain. Published work or contributions in GenAI / LLMs / NLP. Experience with cost optimization for AI workloads and inference serving at scale. Certifications in cloud, AI/ML, etc.
UST is a global digital transformation solutions provider. For more than 20 years, UST has worked side by side with the world's best companies to make a real impact through transformation. Powered by technology, inspired by people and led by purpose, UST partners with their clients from design to operation. With deep domain expertise and a future-proof philosophy, UST embeds innovation and agility into their clients' organizations. With over 30,000 employees in 30 countries, UST builds for boundless impact--touching billions of lives in the process.
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