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About the role
We are seeking a
Senior GenAI / LLM Engineer
to support a contract engagement with a leading financial services organization.
This role focuses on
designing and building production-grade generative AI systems
ā from autonomous AI agents to advanced GraphRAG architectures ā that power enterprise-scale decision-making. You will work at the forefront of applied AI, shipping real products integrated with complex financial data infrastructure.
What you'll do
Build and deploy GenAI applications using foundation models and advanced architectures such as GraphRAG.
Develop autonomous AI agents with modern agentic frameworks.
Design and ship RAG and GenAI services using Python (FastAPI), Docker, and cloud platforms (AWS, Azure, or GCP).
Build scalable REST APIs that power LLM-driven applications integrated with enterprise data sources.
Implement LLM evaluation frameworks ā using tools like Ragas, LangSmith, or custom benchmarks ā to measure answer relevance, groundedness, and hallucination rates.
Apply LLMOps/MLOps best practices: CI/CD pipelines, prompt versioning, automated testing, and monitoring of latency, cost, and response quality.
Build systems leveraging embeddings at scale, knowledge graphs, and ontology extraction.
Collaborate across engineering teams, mentor developers, and help drive innovation in GraphRAG and agentic AI architectures.
What you'll bring
Degree in Computer Science, AI/ML, or a related field.
5+ years of AI/ML-focused software engineering experience.
Production experience building LLM-based or agentic AI systems.
Strong expertise in Python and modern AI frameworks.
Hands-on experience with embeddings, knowledge graphs, ontology extraction, and advanced RAG/GraphRAG implementations.
Full-stack development and deployment experience (Python back end + modern front end).
Proven experience deploying AI workloads to AWS, Azure, or GCP.
Familiarity with LLMOps/MLOps tooling and model evaluation frameworks. xsgimln
Strong problem-solving, communication, and collaboration skills.