AI Engineer at Efinancialcareers

AI Solution Design & Delivery
Build end-to-end agentic AI and LLM-based solutions from concept to deployment
Design AI architectures that map to real business problems in investment banking
Rapidly prototype and iterate AI solutions based on stakeholder feedback
Move quickly from business brief to working solution - velocity is critical
Own delivery independently with minimal supervision
Business Engagement & Requirements:
Engage directly with business stakeholders (traders, analysts, operations, research teams) to understand workflows and pain points
Translate business requirements into AI solution designs
Demonstrate AI capabilities and educate stakeholders on art-of-the-possible
Gather feedback and iterate solutions based on real user needs
Communicate technical concepts to non-technical business audiences
Technical Implementation:
Develop robust Python-based AI applications and agent systems
Integrate LLM capabilities (OpenAI, Anthropic, Azure OpenAI) into business workflows
Build agentic AI systems that can reason, plan, and execute multi-step tasks
Implement RAG (Retrieval-Augmented Generation) pipelines for domain-specific knowledge
Work with vector databases and enterprise data sources
Integrate AI solutions with existing .NET/C# enterprise systems where required
Innovation & Best Practices
Stay current with rapidly evolving LLM and agentic AI landscape
Recommend appropriate AI frameworks and tools for different use cases
Establish best practices for responsible AI deployment in regulated environment
Balance innovation speed with security and compliance requirements
Essential Skills & Experience
AI & LLM Expertise
Proven experience building end-to-end agentic AI or LLM-based solutions in production environments
Deep understanding of LLM capabilities and limitations - knows when AI is (and isn't) the right solution
Experience designing AI solutions that map to real business problems , not just technical demos or proof-of-concepts
Track record of delivering working AI solutions that create business value
Technical Skills
Strong Python development skills - production-quality code, not just notebooks
Ability to architect and build complete AI applications end-to-end
Experience integrating AI capabilities into existing enterprise systems
Understanding of software engineering best practices for AI systems
Desirable Skills & Experience
LLM & AI Frameworks
Experience with specific LLM providers (OpenAI, Anthropic, Azure OpenAI)
Familiarity with agent frameworks such as LangChain, LlamaIndex, AutoGen, or similar
Experience building multi-agent systems and orchestration workflows
Knowledge of prompt engineering and optimization techniques
Technical Depth
C# / .NET background for enterprise integration in financial services
Experience with RAG pipelines and vector databases (Pinecone, Weaviate, ChromaDB, etc.)
Understanding of embedding models and semantic search
Knowledge of fine-tuning and model customization approaches

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