AI Engineer

Job Title: GenAI Developer/ Engineer About Us “Capco, a Wipro company, is a global technology and management consulting firm. Awarded with Consultancy of the year in the British Bank Award and has been ranked Top 100 Best Companies for Women in India 2022 by Avtar & Seramount. With our presence across 32 cities across globe, we support 100+ clients across banking, financial and Energy sectors. We are recognized for our deep transformation execution and delivery. WHY JOIN CAPCO? You will work on engaging projects with the largest international and local banks, insurance companies, payment service providers and other key players in the industry. The projects that will transform the financial services industry. MAKE AN IMPACT Innovative thinking, delivery excellence and thought leadership to help our clients transform their business. Together with our clients and industry partners, we deliver disruptive work that is changing energy and financial services. #BEYOURSELFATWORK Capco has a tolerant, open culture that values diversity, inclusivity, and creativity. CAREER ADVANCEMENT With no forced hierarchy at Capco, everyone has the opportunity to grow as we grow, taking their career into their own hands. DIVERSITY & INCLUSION We believe that diversity of people and perspective gives us a competitive advantage. Location - Bangalore Experience - 6 to 10 Skills and Qualifications: Preferred skills: Programming: Advanced Python (async programming, OOP, REST APIs, FastAPI, Flask, Pandas, NumPy) GenAI Frameworks: LangChain, LlamaIndex, Haystack, Semantic Kernel Machine Learning and AI: Snowflake Cortex, TensorFlow, PyTorch Key Responsibilities: Develop scalable Python applications focused on GenAI Knowledge of Snowflake Cortex is a big plus. Learn and apply techniques like document chunking and embeddings Proficient in both SQL (e.g., PostgreSQL, MySQL) and NoSQL (e.g., MongoDB, Cassandra) databases, including schema design and optimization. Design, develop, and fine-tune applications built around foundation models (e.g., LLMs, multimodal models) for specific business needs Implement and experiment with generative AI techniques, including but not limited to Retrieval-Augment ed Generation (RAG) and prompt engineering Lead the implementation of intelligent autonomous agents and multi-agent systems capable of complex decision-making, task execution, and interaction with external systems Utilize and contribute to agentic AI frameworks (e.g., LangChain, AutoGen, Semantic Kernel, Crew AI) to build robust and scalable AI agents