AI Engineer

Position: AI Engineer

Location: Remote

Duration: 4-6 months

Position Summary

The AI Engineer will design, build, and deploy AI-powered applications and agentic data engineering solutions that automate business processes and improve operational efficiency. This role will be responsible for developing intelligent systems, integrating large language models (LLMs), building API-driven architectures, and creating scalable data pipelines that support AI-enabled business workflows.

The ideal candidate has hands-on experience developing AI applications using modern AI-assisted development tools such as Claude Code, Cursor, and related frameworks, along with strong software engineering and data engineering expertise.

Key Responsibilities

• Design and develop agentic AI solutions that automate complex business processes and operational workflows.
• Build AI-powered applications using modern LLM technologies and AI development platforms, including Claude Code, Cursor, and related tools.
• Architect and implement scalable data engineering products that leverage generative AI and autonomous agents to reduce manual effort and increase productivity.
• Design, develop, and maintain RESTful APIs, service integrations, and connectivity layers between enterprise systems.
• Build and optimize data pipelines for ingestion, transformation, orchestration, and delivery of structured and unstructured data.
• Integrate enterprise systems, databases, SaaS platforms, and third-party services into AI-driven workflows.
• Develop and maintain AI agent frameworks capable of performing multi-step tasks, decision-making, and business process automation.
• Collaborate with business stakeholders, product owners, and technical teams to identify automation opportunities and translate requirements into technical solutions.
• Establish best practices for prompt engineering, model evaluation, observability, testing, and AI application performance monitoring.
• Ensure solutions meet security, privacy, governance, and compliance standards.
• Create technical documentation, architecture diagrams, and operational runbooks to support ongoing maintenance and adoption.
• Participate in code reviews and contribute to engineering standards, scalability, and platform reliability.

Required Qualifications

• 5+ years of software engineering, data engineering, or AI engineering experience.
• Proven experience building AI-enabled applications and business process automation solutions.
• Hands-on experience with Claude Code, Cursor, GitHub Copilot, or similar AI-assisted development tools.
• Strong programming experience in Python and modern software development practices.
• Experience designing and consuming REST APIs and integrating with enterprise applications.
• Experience building and maintaining ETL/ELT pipelines and data integration solutions.
• Familiarity with LLMs, prompt engineering, retrieval-augmented generation (RAG), vector databases, and AI agent frameworks.
• Experience with cloud platforms such as Microsoft Azure, AWS, or Google Cloud Platform.
• Strong understanding of software architecture, security, authentication, and scalability principles.
• Excellent problem-solving, collaboration, and communication skills.

Preferred Qualifications

• Experience with frameworks such as LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen, or similar agentic AI platforms.
• Experience with Azure OpenAI Service, Anthropic Claude APIs, OpenAI APIs, or other commercial LLM platforms.
• Knowledge of containerization and deployment technologies such as Docker and Kubernetes.
• Experience implementing AI governance, model monitoring, and responsible AI practices.
• Prior experience delivering AI solutions in enterprise environments.

Deliverables

• Agentic AI solutions that automate targeted business processes.
• Production-ready AI applications and supporting services.
• Secure API integrations and connectivity frameworks.
• Automated data pipelines and workflow orchestration components.
• Technical documentation, architecture artifacts, and deployment guides.
• Knowledge transfer to client stakeholders and technical teams.