Capco - AI Engineer
Requirements
• 3–12 years of professional experience in AI/ML engineering, with a focus on software development and deployment. • AI/ML engineering • Build and integrate components for LLM, RAG, search, agent-based and automation solutions, • LLM, RAG, search, agent-based • Strong software engineering experience with Python, Java, React Next, Node.js • Python, Java, React Next, Node.js • Hands-on experience training and fine-tuning neural network models, with a track record of optimizing for performance and scalability. • Proven expertise working with LLMs (e.g., GPT, BERT) and building agentic solutions using frameworks like LangChain, LangGraph, or ADK. • LangChain, LangGraph, • Familiarity with cloud platforms (AWS, Azure, or Google Cloud) for model deployment and data management. • Solid understanding of machine learning concepts, including supervised/unsupervised learning, evaluation metrics, and bias mitigation. • Experience with version control systems (e.g., Git) and agile methodologies. • Excellent problem-solving skills and ability to work in a fast-paced, collaborative environment. • Experience in financial services domains • Familiarity with big data tools (e.g., Spark, Hadoop) and databases (SQL/NoSQL). • Knowledge of graph databases and knowledge graphs. • Understanding DevOps practices, containerization (Docker, Kubernetes), and MLOps workflows. • Publications, open-source contributions, or certifications in AI/ML. • Strong communication skills for presenting technical concepts to non-technical stakeholders.
Responsibilities
• Build multi-agent workflows to optimize business processes within insurance. • Develop and maintain software pipelines for data processing, model training, and deployment using Python-based frameworks. • Train, fine-tune, and optimize neural network models, including LLMs, for specific use cases such as risk assessment and customer query resolution. • Collaborate with data scientists, engineers, and business stakeholders to translate requirements into production-ready AI applications. • Ensure AI models adhere to banking regulations, data privacy standards (e.g., GDPR, CCPA), and ethical AI practices. • Monitor deployed solutions in production, troubleshooting issues, and implement updates as needed. • Strong experience delivering production-grade applications, backend services and technical components that support data, workflow, automation or AI-driven solutions. • Participate in code reviews, agile ceremonies, and CI/CD processes.
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