AI Application Developer

We are seeking an experienced Senior/Lead Applications Developer with strong hands-on expertise in Artificial Intelligence, Generative AI, and enterprise application development. This role will focus on identifying, designing, and implementing AI solutions to reduce administrative workload, improve operational efficiency, and enhance quality., The ideal candidate will bridge business operations and technology, translating complex business processes into technical requirements and developing secure, custom AI solutions within a controlled enterprise environment. The role involves evaluating existing enterprise AI platforms and building tailored solutions using Python, Azure AI, Google Cloud/Vertex AI, and other approved technologies.

• Bachelor’s degree in a related field with 10+ years of programming and application development experience, or equivalent experience. \n

• Strong hands-on experience developing AI/LLM-based applications and solutions. \n

• Proficiency in Python, SQL, and C#/.NET Framework. \n

• Experience with Azure OpenAI, Azure AI Foundry, or comparable enterprise AI platforms. \n

• Strong knowledge of Generative AI, LLMs, embeddings, vector databases, prompt engineering, and RAG architectures. \n

• Experience building and integrating AI agents and custom AI solutions. \n

• Understanding of cloud architecture, particularly Azure compute, storage, networking, and AI services. \n

• Knowledge of MLOps, AI lifecycle management, CI/CD, and AI governance. \n

• Experience evaluating AI outputs for accuracy, bias, hallucinations, privacy, and security risks. \n

• Familiarity with Responsible AI principles, including fairness, reliability, safety, privacy, inclusiveness, transparency, and accountability. \n

• Experience with multiple programming languages, database management systems, development platforms, and system integrations. \n

• Strong understanding of Agile methodologies and software development best practices. \n

• Excellent analytical, problem-solving, communication, and technical documentation skills. \n

• Ability to work independently, prioritize multiple tasks, and collaborate effectively with cross-functional teams. \n, * Master’s degree in a related field. \n

• Experience with Google Cloud, Vertex AI, Gemini, and NotebookLM. \n

• Experience with Azure Machine Learning Responsible AI Dashboard and Azure AI Content Safety. \n

• Familiarity with fine-tuning foundation models and implementing AI evaluation frameworks. \n

• Experience using GitHub Copilot for enterprise development and testing. \n

• Knowledge of Microsoft Responsible AI Standards and enterprise AI compliance frameworks. \n

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• Analyze business processes and operational requirements to identify opportunities for AI-driven automation and improvement. \n

• Translate business needs into detailed technical specifications, architecture designs, and actionable development requirements. \n

• Evaluate existing enterprise AI tools, including Gemini and NotebookLM, versus developing custom AI solutions. \n

• Architect, prototype, develop, test, and deploy secure AI applications within enterprise environments. \n

• Design and implement Generative AI solutions using LLMs, prompt engineering, RAG pipelines, embeddings, vector databases, and AI agents. \n

• Develop and integrate AI solutions using Azure OpenAI, Azure AI Foundry, Google Cloud/Vertex AI, and approved enterprise platforms. \n

• Implement AI guardrails, content safety controls, and responsible AI practices to minimize bias, hallucinations, and security vulnerabilities. \n

• Utilize AI-assisted development tools such as GitHub Copilot to accelerate coding, documentation, and testing. \n

• Follow Agile development practices and participate in the complete software development lifecycle, including analysis, design, coding, testing, deployment, and maintenance. \n

• Conduct unit, system, and user acceptance testing; analyze results and resolve technical issues. \n

• Maintain comprehensive technical documentation covering code, architecture, system prompts, workflows, and integrations. \n

• Collaborate with business stakeholders, technical teams, and leadership to communicate AI capabilities, limitations, and implementation strategies. \n

• Ensure solutions align with enterprise security, privacy, governance, and compliance standards. \n

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