AI Programmer Analyst
@ PB consultingAI Programmer Analyst
About the job
The company specializes in enterprise solutions leveraging AI. The AI Programmer Analyst role focuses on designing, developing, and deploying AI applications that solve complex business challenges and enhance operational efficiency.
Requirements
- 2–10 years in software or AI development
- Experience with LLMs and RAG
- Proficient in Python and AI libraries
- Integrate AI with APIs and databases
- Knowledge of cloud AI platforms
Qualifications
- Bachelor's in CS, IT, Engineering, Data Science
- Strong problem-solving skills
- Good communication and documentation abilities
- Experience with AI/ML concepts and frameworks
- Ability to work in team environments
Full job description
Job Summary
We are seeking an experienced AI Programmer Analyst to design, develop, and implement enterprise AI solutions that solve complex business challenges and improve operational efficiency. The ideal candidate will have hands-on experience building AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and enterprise AI platforms. This role involves collaborating with business and technology teams to deliver scalable, secure, and responsible AI solutions from concept through production deployment.
Roles and Responsibilities
- Partner with business and technology stakeholders to identify, evaluate, and implement AI-driven solutions.
- Design, prototype, develop, test, deploy, and maintain enterprise AI applications and intelligent automation solutions.
- Evaluate and select appropriate AI models, frameworks, and architectures based on business and technical requirements.
- Develop and optimize prompts, AI agents, workflows, orchestration pipelines, and retrieval strategies to improve solution accuracy and effectiveness.
- Integrate AI solutions with enterprise applications, APIs, databases, and business processes.
- Build scalable AI solutions leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and agent-based architectures.
- Design AI-powered monitoring pipelines that analyze application, server, and database logs to predict system anomalies, recommend real-time resolutions, and automate root-cause analysis.
- Monitor AI model performance, reliability, accuracy, and adoption while continuously improving deployed solutions.
- Ensure AI solutions comply with security, governance, privacy, and Responsible AI standards.
- Create technical documentation, architecture diagrams, implementation guides, and operational runbooks.
- Participate in CI/CD processes, source control, testing, and DevOps practices for AI application delivery.
- Research and recommend emerging AI technologies, frameworks, and best practices.
Required Skills
- 2–10 years of experience in software development, AI application development, or machine learning engineering.
- Strong experience with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, prompt engineering, and AI orchestration frameworks.
- Hands-on experience with enterprise AI platforms such as Azure AI, Microsoft Copilot Studio, Gemini Enterprise, or similar AI services.
- Strong Python programming skills with AI/ML libraries and frameworks.
- Experience integrating AI solutions with enterprise applications, REST APIs, databases, and cloud platforms.
- Strong SQL and data analysis skills.
- Experience with cloud-based AI services and enterprise AI platforms.
- Solid understanding of AI/ML concepts, model evaluation techniques, model limitations, and Responsible AI practices.
- Experience with Git, version control, DevOps, and CI/CD pipelines.
- Strong analytical, problem-solving, communication, and documentation skills.
Preferred Skills
- Experience implementing AIOps solutions for predictive log analysis, automated incident remediation, and root-cause analysis.
- Experience with monitoring and observability platforms.
- Familiarity with MLOps practices, model deployment, monitoring, and lifecycle management.
- Experience developing scalable AI applications in cloud environments.
Education
- Bachelor's degree in Computer Science, Information Technology, Engineering, Data Science, or a related field (or equivalent experience).
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