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AI Engineer, Malvern, PA, US
Job Description
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
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.
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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.
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Job Responsibilities
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.
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