Objectives of the role:
- 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.
Required Skills & Qualifications:
- 7 years + of experience in AI engineering or 8+ 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
