div:has([data-free-thinking-preview-answer=true])+:is(.text-message,.relative:has(>.text-message))]:-mt-2 grow">
Job Summary
The Machine Learning / Agentic AI Engineer / Tech Lead will design, develop, and deploy enterprise AI agents and agentic AI solutions using Python and modern Generative AI technologies. The role will focus on building multi-agent systems, developing RAG solutions, integrating AI agents with enterprise applications and APIs, and improving reliability, observability, and performance. The position requires strong hands-on Agentic AI and Python experience, along with the ability to provide technical leadership and contribute to enterprise AI platform architecture.
Key Responsibilities
• Design, develop, and deploy AI agents for enterprise use cases.
• Build multi-agent systems capable of coordinating and executing tasks autonomously.
• Develop Agentic AI workflows using modern AI orchestration frameworks.
• Design, develop, and optimize Retrieval-Augmented Generation (RAG) solutions.
• Integrate AI agents with APIs, internal platforms, monitoring tools, and enterprise applications.
• Build scalable backend services using Python.
• Improve the reliability, observability, scalability, and performance of AI agents and workflows.
• Collaborate with platform, infrastructure, and operations teams to integrate and operationalize AI solutions.
• Contribute to the architecture and evolution of enterprise AI platforms.
• Provide technical leadership, architectural guidance, and engineering best practices across Agentic AI initiatives.
• Evaluate emerging AI technologies and frameworks and identify opportunities for enterprise adoption.
Required Qualifications
• 10+ years of overall professional software engineering or technology experience.
• 8+ years of software engineering experience for Tech Lead-level responsibilities.
• Strong hands-on Python development experience.
• 3+ years of Generative AI and/or LLM engineering experience for Tech Lead-level responsibilities.
• Hands-on experience building Generative AI or Agentic AI applications.
• Experience with one or more Agentic AI or orchestration frameworks such as LangGraph, LangChain, CrewAI, AutoGen, or Semantic Kernel.
• Experience working with LLM platforms and models such as OpenAI, Azure OpenAI, Anthropic, or AWS Bedrock.
• Proven experience designing and implementing RAG solutions.
• Experience developing APIs and enterprise integrations.
• Experience with at least one major cloud platform, including AWS, Azure, or GCP.
• Experience with software architecture and technical leadership.
• Strong understanding of scalable backend services and enterprise application integration.
• Strong problem-solving, communication, and collaboration skills.
Preferred Qualifications
• Experience developing and managing multi-agent systems.
• Experience with vector databases and semantic search.
• Experience with MLOps or LLMOps practices.
• Experience with Kubernetes and containerization technologies.
• Experience with observability tools such as Datadog or Grafana.
• Experience with Site Reliability Engineering (SRE) practices.
• Experience developing Slack integrations or ChatOps solutions.
• Experience developing and operating enterprise-scale AI platforms.
