AI Engineer

We are looking for a visionary AI Engineer to lead the integration of advanced artificial intelligence into our flagship products. You will be at the forefront of innovation, designing proprietary AI tools, executing high-impact Proof of Concepts (POCs), and architecting the data structures necessary for robust AI/ML scaling.

Technical Stack & Requirements: AI/ML Stack: Amazon SageMaker, AWS Bedrock. Design Focus: Vector databases, knowledge graphs, and semantic layers. Databricks: Experience with Databricks and Databricks Genie is highly desirable. Core Mandate: Define the standards for “AI-ready” data curation and direct the integration of AI methodologies into existing Service Experience and Financials business logic. Qualifications: 6-8+ years of experience. Strong background in AI/ML design and implementation. Ability to architect semantic layers and knowledge graphs. Experience with GitHub Actions for managing codebases. Required Qualifications Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related field. 8+ years of software engineering experience. 3+ years of hands-on AI/ML engineering experience. Advanced Python programming skills. Strong experience building production-grade AI applications. Experience with Generative AI and Large Language Models. Experience designing Retrieval-Augmented Generation (RAG) architectures. Knowledge of vector databases and embedding models. Experience deploying AI solutions on AWS cloud platforms. Experience with CI/CD pipelines and DevOps practices. Strong understanding of distributed systems and scalable backend architectures. Excellent communication and stakeholder management skills. Preferred Qualifications Experience with Agentic AI frameworks (LangGraph, AutoGen, CrewAI, Semantic Kernel). Experience with AWS Bedrock, Amazon SageMaker, Azure OpenAI, or Vertex AI. Experience implementing Responsible AI frameworks. Financial services, fintech, or investment management domain experience. Experience building recommendation engines, intelligent assistants, or AI copilots. Knowledge of Kubernetes, Docker, and cloud-native microservices. AWS AI/ML certifications or equivalent.