Our Client Currently looking for Senior AI Engineer
What You’ll Do:
LLM & AI Pipeline Engineering
- Design, build, and maintain production-grade LLM integration pipelines — including retrieval-augmented generation (RAG), prompt engineering, output parsing, and chain orchestration.
- Develop and operate AI features within Jeeves’s core financial products: spend categorization, document extraction, anomaly detection, financial Q&A, and automated reconciliation.
- Implement structured output validation, fallback handling, and confidence scoring to ensure AI decisions meet reliability standards for financial use cases.
- Evaluate and integrate AI frameworks and tools (LangChain, LlamaIndex, OpenAI API, Anthropic API, HuggingFace, vector databases) and advocate for the right tool for the job.
- Establish prompt versioning and evaluation practices to ensure AI outputs remain accurate and consistent as models and data evolve.
Retrieval & Vector Search
- Design and maintain vector search pipelines using databases such as Pinecone, Weaviate, or pgvector to power semantic search and RAG-based features.
- Build document ingestion and chunking pipelines for financial data — processing invoices, receipts, policy documents, and transaction records.
- Optimize retrieval quality through embedding model selection, chunk strategy, metadata filtering, and re-ranking techniques.
ML Model Serving & Operations
- Collaborate with data scientists to take trained ML models from experimental notebooks to production serving infrastructure.
- Build and maintain model serving endpoints with appropriate latency SLOs, input validation, and output monitoring.
- Implement model performance monitoring and data drift detection to ensure production models remain accurate over time.
- Support model retraining workflows by designing clean data pipelines and feature engineering that can be continuously updated.
Backend Integration & Reliability
- Integrate AI services cleanly with Jeeves’s backend microservices — designing clear API contracts, circuit breakers, and graceful degradation patterns.
- Write high-quality, testable backend code in Python or Go/Node.js to power AI-integrated features.
- Instrument AI components with structured logging, distributed tracing, latency dashboards, and alerting to ensure operational visibility.
- Build human-in-the-loop review workflows for AI decisions that require oversight — particularly for high-value financial actions.
Collaboration & Growth
- Partner with Product, Backend Engineering, and Data Science to define the AI roadmap and translate requirements into reliable systems.
- Contribute to a culture of quality by writing design docs, reviewing peers’ AI system designs, and sharing learnings openly.
- Help grow the AI engineering practice at Jeeves by establishing patterns, tooling, and best practices that the broader team can build on.
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Are you interested in this position?
Apply by clicking on the “Apply Now” button below!
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