Job Summary

• Design, develop, and deploy production-ready AI solutions that integrate seamlessly into enterprise applications and business workflows.
• Build scalable AI platforms and reusable components to accelerate AI adoption across multiple business functions.
• Develop intelligent AI copilots, conversational assistants, and autonomous agent systems that improve operational efficiency and customer experience.
• Establish best practices for AI engineering, MLOps, governance, monitoring, and responsible AI implementation.

Key Responsibilities

• Design and implement AI-powered applications, APIs, and services using modern software engineering practices.
• Develop and deploy generative AI, and agentic AI solutions for business and customer-facing use cases.
• Design and build autonomous and semi-autonomous AI agent systems capable of planning, reasoning, tool usage, and workflow automation.
• Implement multi-agent architectures for complex business processes requiring collaboration between specialized AI agents.
• Integrate AI systems with enterprise tools, APIs, databases, and business applications.
• Develop evaluation and guardrail mechanisms to ensure reliability, safety, accuracy, and compliance.
• Optimize model latency, token consumption, infrastructure utilization, and operational costs.
• Ensure AI solutions comply with enterprise governance, security, privacy, and regulatory requirements.

Skill Requirements

• 3 years + of experience in AI engineering or 5+ years of experience in software engineering, machine learning engineering or related disciplines
• Strong programming experience in Python and familiarity with software engineering best practices.
• Hands-on experience building and deploying LLM-based applications and generative AI solutions.
• Experience with AI orchestration and agent frameworks such as LangGraph.
• Experience designing and deploying RAG architecture, vector databases, multi-agent systems
• Experience with developing on Microsoft Azure.

Other Requirements