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Build and maintain scalable data pipelines and cloud data platforms for banking clients, using Spark, Scala, and cloud services to deliver clean, governed data for analytics and AI.
Build and deploy ML models and data pipelines for a financial-services client’s new AI practice using Python, Spark, Hadoop, and SQL.
Build LLM-powered automations, chat/voice assistants, and RAG pipelines using Python, FastAPI, and vector databases; deploy cloud-native services with CI/CD and guardrails.
Build and ship AI-powered web apps and agents using LLMs, Python/Node.js, and cloud tools; integrate AI into marketing platforms and internal tools for measurable business impact.
Build and secure data pipelines for a banking client, using Scala, Spark, and cloud platforms to process large-scale data into reliable, business-ready datasets.
Principal engineer defining and building next-gen AI agent platforms on Oracle Cloud Infrastructure, leading multi-team execution and hands-on design of scalable, secure, and cost-aware agentic systems.
Build and maintain full-stack .NET applications using C#, ASP.NET Core, and Entity Framework, while integrating AI tools like OpenAI and vector databases.
Build and ship the AI backbone for a property-management assistant: RAG pipelines, multi-step agent workflows, and LLM integrations that power daily operations for 20,000+ HOA and condo communities.
Lead the architecture and development of large-scale RAG and NLP systems for vertical AI platforms, using PyTorch, vector databases, and probabilistic modeling to deliver predictive intelligence for high-stakes industries.
Build and maintain Python-based backend services for an AI tool that streamlines pharmaceutical regulatory reviews using FastAPI, PostgreSQL, Celery, and Azure.
Principal Data Engineer builds and scales AI-native data infrastructure for LLM-powered security products, including RAG and agentic systems at Exabyte scale.
Principal Data Engineer designs and builds scalable cloud data pipelines using Snowflake, Databricks, and AWS, while integrating AI agents for automated data quality and transformation workflows.
Build and deploy Python-based AI solutions, integrating LLMs and RAG architectures with vector databases for enterprise clients in a hybrid Warsaw role.
Build and deploy Python-based AI solutions, integrating LLMs and RAG architectures with vector databases for production use in a global consulting firm undergoing AI transformation.
Senior Python developer building AI/GenAI solutions, integrating LLMs and RAG pipelines, and moving POCs to production in a financial IT environment.
Build and deploy Generative AI systems for financial applications, including RAG pipelines, vector databases, and AI agents, using Python, AWS Bedrock, and LangGraph.
Builds scalable Python backend services and full-stack apps with Django/FastAPI, integrates Generative AI models, and engineers data pipelines for enterprise clients.
Build and tune LLM-based AI agents and RAG systems for ERP automation and SaaS knowledge bases, using Python, PyTorch, LangChain, and cloud pipelines.
Design and build AI-agent workflows, integrating models, memory, and tools; set reliability standards and evaluation tooling for production systems.
Senior Full-Stack Engineer building an AI-powered financial crime investigation platform in fintech, using React, Python, FastAPI, LangGraph, and AWS.
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