Hire Suleman A. - AI Engineer - New York

Design and deploy internal RAG pipelines leveraging OCR, and custom VLM plugins to enhance enterprise knowledge retrieval, driving improvements in extraction precision and response accuracy across large-scale proprietary document corpora. - Execute LLM evaluation frameworks using LangChain, LlamaIndex, and OpenAI/Anthropic APIs to benchmark model performance against internal documentation, achieving 90% accuracy, aligned with industry-standard benchmarks. - Lead the end-to-end vision and delivery of a multi-agent AI platform — defining technical strategy, aligning cross-functional stakeholders, and overseeing architecture, orchestration, and production deployment.

Develop end-to-end automated solutions integrating UiPath and OCR pipelines for document entity extraction, reducing manual processing time by 40% and streamlining client digitization. - Support RFI responses by proposing innovative Generative AI solutions leveraging Gemini LLMs and RAG architectures to accelerate document understanding for federal clients. - Design and deploy custom AI agents, leveraging LangGraph orchestration, integrating with Salesforce API to automate task creation, reducing client operations workload by 30%. - Engineer Python scripts to generate synthetic test datasets, enabling comprehensive testing of DocAI’s capabilities on 200+ document variations.

* Develop end-to-end automated solutions integrating UiPath and OCR pipelines for document entity extraction, reducing manual processing time by 40% and streamlining client digitization. * Support RFI responses by proposing innovative Generative AI solutions leveraging Gemini LLMs and RAG architectures to accelerate document understanding for federal clients. * Design and deploy custom AI agents, leveraging LangGraph orchestration, integrating with Salesforce API to automate task creation, reducing client operations workload by 30%. * Engineer Python scripts to generate synthetic test datasets, enabling comprehensive testing of DocAI’s capabilities on 200+ document variations. * Collaborate with federal clients to identify business requirements and communicate technical solutions, resulting in 95% client satisfaction rate. * Develop and implement machine learning algorithms such as neural network models, to analyze client data, resulting in a 30% increase in predictive accuracy and a 40% reduction in data processing time. * Optimize ETL jobs by administering performance tuning techniques, resulting in a 50% reduction in job execution time.