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Overview
LABUR is partnering with a client to identify a Senior AI/ML Developer who will design, develop, and deploy AI-powered applications and cloud-native services. This role centers on building and optimizing Large Language Model (LLM) solutions, Retrieval-Augmented Generation (RAG) pipelines, and AI orchestration frameworks within a Microsoft Azure environment. The ideal candidate brings 6-10 years of development experience and a drive to leverage cutting-edge AI technologies to solve complex enterprise challenges.
Responsibilities
Design, develop, and deploy AI-powered applications and cloud-native services supporting the enterprise AI platform.
Build and optimize backend services using Azure Functions and modern cloud technologies.
Develop, integrate, and optimize LLM solutions, prompt engineering techniques, RAG pipelines, and AI orchestration frameworks.
Develop and maintain CI/CD pipelines using GitLab, Terraform, and infrastructure-as-code best practices.
Build secure integrations with enterprise applications, APIs, and data sources while adhering to enterprise architecture and security standards.
Design and optimize data models using Cosmos DB and JSON-based data structures to power high-performance AI applications.
Troubleshoot complex technical issues, optimize application performance, and continuously elevate software quality and reliability.
Contribute to architecture discussions, code reviews, and technical documentation while mentoring junior developers in AI/ML engineering and cloud development practices.
Qualifications
6-10 years of hands-on software engineering experience designing and developing enterprise applications.
Strong proficiency developing cloud-native applications on Microsoft Azure, including Azure Functions, Azure AI services, and secure networking with Private Endpoints; proven experience building and maintaining CI/CD pipelines using GitLab, Terraform, and Infrastructure-as-Code practices.
Experience building AI-enabled applications using Large Language Models (Azure OpenAI, OpenAI, or similar), prompt engineering, RAG, semantic search, embeddings, and agentic AI workflows; hands-on experience with AI-accelerated engineering practices including agentic code generation tooling such as Claude, Copilot, and Codex.
Strong Python development skills for AI workflows, automation, backend services, and data processing; experience developing data-intensive applications using Cosmos DB and JSON document storage with the ability to integrate structured and unstructured data sources.
Proven experience developing and maintaining CI/CD pipelines using GitLab, Terraform, and Infrastructure-as-Code practices.
Solid understanding of data governance, security, enterprise integration patterns, and modern software engineering principles including object-oriented design, testing strategies, version control, and secure coding practices.
Demonstrated success working within Agile teams alongside architects, developers, product owners, and business stakeholders with the ability to translate business requirements into scalable AI and software solutions.
Excellent written and verbal communication skills with the ability to explain technical concepts to both technical and non-technical audiences and collaborate effectively across engineering and business teams.
Preferred Qualifications
Experience building enterprise Generative AI solutions using Azure OpenAI, LangChain, Semantic Kernel, AutoGen, or similar AI orchestration frameworks.
Experience developing RAG applications and vector database implementations.
Familiarity with AI governance, model evaluation, responsible AI, prompt optimization techniques, and enterprise-scale API integrations and security frameworks.