K&L Gates
Agentic Artificial Intelligence Engineer Developer II
K&L Gates, Chicago, Illinois, United States, 60290
Job Description
At K&L Gates, we are looking for smart, imaginative and hard-working people with diverse backgrounds, experiences and ideas to join us. Perhaps our search for talented visionaries and your search for important and impactful work lead to the same place.
We are seeking a senior-level AI Developer with deep expertise in Retrieval-Augmented Generation (RAG) architectures, semantic search, reranking algorithms, and vectorization techniques. The ideal candidate will be hands-on with Python, Docker, and Azure AI services, and capable of building scalable, secure, and production-grade AI applications for legal and enterprise automation.
Core Responsibilities
Architect and implement RAG pipelines using Azure AI Search, OpenAI embeddings, and custom reranking logic.
Develop and deploy containerized AI applications using Docker and Azure Container Apps.
Build semantic search systems with hybrid retrieval, chunking, enrichment, and vector indexing.
Integrate NLP workflows for document ingestion, summarization, and entity extraction using Azure AI Language and Document Intelligence.
Implement reranking models using transformer-based scoring and feedback loops.
Manage vector stores (e.g., Azure Cosmos DB, Azure SQL, or FAISS) for low-latency retrieval.
Design and maintain FastAPI-based microservices for inference and orchestration.
Collaborate with DevOps to automate deployment using Azure Developer CLI (azd), Bicep, and GitHub Actions.
Ensure security and governance using Azure Key Vault, RBAC, private endpoints, and Purview policies.
Monitor and evaluate model performance using Foundry Observability and Application Insights.
Required Skills
Expert-level Python (including LangChain, FastAPI, PyTorch / TensorFlow).
Strong understanding of RAG architecture and semantic search principles.
Experience with Azure AI Search, Azure OpenAI, Azure AI Foundry, and Azure Document Intelligence.
Hands-on with Docker, GitHub Codespaces, and container orchestration.
Familiarity with reranking techniques (BM25, neural rerankers, hybrid scoring).
Proficiency in NLP tasks: tokenization, chunking, summarization, NER, sentiment analysis.
Experience with vector databases and embedding models.
Knowledge of Azure DevOps, Bicep, Terraform, and CI / CD pipelines.
Strong grasp of security best practices in AI systems (private endpoints, RBAC, secrets management).
Preferred Qualifications
Prior experience in legal tech or document automation.
Familiarity with Azure Machine Learning for fine-tuning and MLOps.
Experience with agentic applications and multi-turn AI agents.
Exposure to compliance frameworks and secure AI deployment.
Compensation Salary $98,000 - $183,000 The compensation salary for this position will be determined during the interview process and will vary based on multiple factors, including but not limited to prior experience, relevant expertise, current business needs, and market factors.
ABOUT THE FIRM K&L Gates is a fully integrated global law firm with lawyers located across five continents in more than 40 offices. We have experienced dramatic growth in the past decade and now rank among the largest U.S. based law firms in the world. We take pride in constantly striving for innovation, imagination and an entrepreneurial spirit. We come up with big ideas and then roll up our sleeves to get the job done, guiding our clients through their most complex issues in a variety of industry sectors and across multiple regions of the world.
The industry recognition the firm has garnered emanates from the foundation of a global community aligned on behalf of our clients. The people at K&L Gates are committed to working together to create a legacy for each other, the firm, our clients, and the communities in which we serve. We thrive in an inclusive and socially conscious environment that embraces diversity and takes a holistic approach to the career evolution of all our professionals.
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We are seeking a senior-level AI Developer with deep expertise in Retrieval-Augmented Generation (RAG) architectures, semantic search, reranking algorithms, and vectorization techniques. The ideal candidate will be hands-on with Python, Docker, and Azure AI services, and capable of building scalable, secure, and production-grade AI applications for legal and enterprise automation.
Core Responsibilities
Architect and implement RAG pipelines using Azure AI Search, OpenAI embeddings, and custom reranking logic.
Develop and deploy containerized AI applications using Docker and Azure Container Apps.
Build semantic search systems with hybrid retrieval, chunking, enrichment, and vector indexing.
Integrate NLP workflows for document ingestion, summarization, and entity extraction using Azure AI Language and Document Intelligence.
Implement reranking models using transformer-based scoring and feedback loops.
Manage vector stores (e.g., Azure Cosmos DB, Azure SQL, or FAISS) for low-latency retrieval.
Design and maintain FastAPI-based microservices for inference and orchestration.
Collaborate with DevOps to automate deployment using Azure Developer CLI (azd), Bicep, and GitHub Actions.
Ensure security and governance using Azure Key Vault, RBAC, private endpoints, and Purview policies.
Monitor and evaluate model performance using Foundry Observability and Application Insights.
Required Skills
Expert-level Python (including LangChain, FastAPI, PyTorch / TensorFlow).
Strong understanding of RAG architecture and semantic search principles.
Experience with Azure AI Search, Azure OpenAI, Azure AI Foundry, and Azure Document Intelligence.
Hands-on with Docker, GitHub Codespaces, and container orchestration.
Familiarity with reranking techniques (BM25, neural rerankers, hybrid scoring).
Proficiency in NLP tasks: tokenization, chunking, summarization, NER, sentiment analysis.
Experience with vector databases and embedding models.
Knowledge of Azure DevOps, Bicep, Terraform, and CI / CD pipelines.
Strong grasp of security best practices in AI systems (private endpoints, RBAC, secrets management).
Preferred Qualifications
Prior experience in legal tech or document automation.
Familiarity with Azure Machine Learning for fine-tuning and MLOps.
Experience with agentic applications and multi-turn AI agents.
Exposure to compliance frameworks and secure AI deployment.
Compensation Salary $98,000 - $183,000 The compensation salary for this position will be determined during the interview process and will vary based on multiple factors, including but not limited to prior experience, relevant expertise, current business needs, and market factors.
ABOUT THE FIRM K&L Gates is a fully integrated global law firm with lawyers located across five continents in more than 40 offices. We have experienced dramatic growth in the past decade and now rank among the largest U.S. based law firms in the world. We take pride in constantly striving for innovation, imagination and an entrepreneurial spirit. We come up with big ideas and then roll up our sleeves to get the job done, guiding our clients through their most complex issues in a variety of industry sectors and across multiple regions of the world.
The industry recognition the firm has garnered emanates from the foundation of a global community aligned on behalf of our clients. The people at K&L Gates are committed to working together to create a legacy for each other, the firm, our clients, and the communities in which we serve. We thrive in an inclusive and socially conscious environment that embraces diversity and takes a holistic approach to the career evolution of all our professionals.
#J-18808-Ljbffr