Senior AI Engineer - Remote / Telecommute

• Responsible for designing, developing, and deploying production-grade AI applications and agentic systems powered by large language models.
• The role focuses on building scalable AI solutions, implementing retrieval-augmented generation pipelines, integrating intelligent systems with enterprise platforms, and driving reliable and high-performing AI architectures.

Responsibilities:

• Architect and deliver end-to-end LLM-powered applications and agentic workflows using Python.
• Design and implement RAG pipelines using enterprise data, embeddings, and vector databases.
• Build multi-step, tool-using AI agents with planning, execution, and memory capabilities.
• Utilize frameworks such as LangChain, LangGraph, and AutoGen for agent orchestration.
• Integrate AI systems with APIs, backend services, and cloud platforms.
• Establish evaluation, reliability, scalability, and performance strategies for AI solutions.
• Optimize AI systems for accuracy, latency, and operational efficiency.
• Design scalable cloud-based architectures for AI applications.
• Collaborate with cross-functional teams to deliver intelligent enterprise solutions.
• Support deployment, monitoring, troubleshooting, and enhancement of AI-powered systems.

Requirement/Must Have:

• Strong expertise in Python development.
• Experience building and deploying production-grade backend systems.
• Hands-on experience developing applications using large language models.
• Experience with prompt engineering and orchestration techniques.
• Proven experience with RAG architectures, embeddings, and vector databases.
• Experience with agentic frameworks such as LangChain, LangGraph, or AutoGen.
• Strong system design and scalable application architecture skills.
• Experience building and scaling cloud-based applications.
• Strong analytical and problem-solving skills.
• Excellent communication and collaboration abilities.

Should Have:

• Experience integrating AI systems with enterprise APIs and backend services.
• Knowledge of AI evaluation and monitoring strategies.
• Experience optimizing AI systems for performance, reliability, and cost efficiency.
• Familiarity with enterprise AI deployment and operational best practices.

Skills:

• Python.
• Large Language Models.
• Prompt engineering.
• RAG architectures.
• Embeddings and vector databases.
• LangChain.
• LangGraph.
• AutoGen.
• Agentic AI systems.
• API integration.
• Cloud application development.
• Backend system development.
• AI orchestration.
• System design and scalability.
• Performance optimization.

Qualification And Education:

• Bachelor s degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or related field preferred.
• Advanced certifications or experience in AI/ML technologies preferred.