Agentic AI Engineer - Financial Services
Role Overview
Designs, develops, and deploys enterprise-grade Generative AI applications and autonomous agent-based solutions.
Builds LLM-powered applications, Retrieval-Augmented Generation systems, and multi-agent workflows using modern frameworks and Azure AI services.
Key Skills for This Role
Full Job Posting
Role overview
Designs, develops, and deploys enterprise-grade Generative AI applications and autonomous agent-based solutions.
Builds LLM-powered applications, Retrieval-Augmented Generation systems, and multi-agent workflows using modern frameworks and Azure AI services.
Key responsibilities
- Design and develop Generative AI applications leveraging Large Language Models.
- Build and optimize Agentic AI workflows using frameworks such as LangChain and LangGraph.
- Develop scalable RAG architectures using vector databases and Azure Cognitive Search.
- Integrate foundation models from Azure OpenAI, OpenAI, Anthropic, or open-source platforms.
- Design prompt-engineering strategies and orchestration pipelines for enterprise use cases.
- Collaborate with business stakeholders to translate requirements into AI-driven solutions.
- Evaluate application performance and improve response quality, latency, and accuracy.
- Implement monitoring, governance, and responsible AI practices.
- Support deployment and productionization of AI applications in cloud environments.
Required skills
- Strong proficiency in Python, LLM integration, prompt engineering, and RAG architectures.
- Hands-on experience with LangChain, LangGraph, CrewAI, AutoGen, or similar frameworks.
- Experience with API integration, microservices development, and vector databases such as FAISS, Pinecone, Chroma, or Weaviate.
- Experience with Azure OpenAI Services and Azure Cognitive Search.
- Understand AI application security, scalability, and monitoring.
Preferred skills
- Exposure to LLM fine-tuning techniques and knowledge of model evaluation methodologies.
- Financial services, banking, or fintech experience preferred.
- Experience with containerization tools such as Docker or Kubernetes preferred.
Qualifications
- Bachelor's or master's degree in computer science, Artificial Intelligence, Data Science, or a related field.
- At least 3 years of software development experience.
- At least 2 years of experience building AI or GenAI solutions.
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