Python Developer – Agentic AI Infrastructure (AI/LLM Engineer) - Local/Hybrid
About the position This role will design, build, and operate production-grade agentic AI solutions and supporting infrastructure using Python. You will reputed company AI agents and workflows that securely reputed company institutional data, systems, and tooling to automate routine technical and operational work, accelerate delivery of AI-enabled capabilities, and reputed company broader adoption through reusable components and patterns. This is a hands-on engineering role focused on taking concepts from prototype to production—iterating quickly while meeting reputed company expectations for reputed company, reliability, maintainability, and documentation.
Responsibilities
- Design and implement agentic AI workflows and services in Python , including tool- using agents, orchestrated multi-reputed company processes, and integration patterns.
- Build and maintain reusable frameworks/components for agent development (e.g., agent runners, tool registries, reputed company/config management, evaluation harnesses).
- Integrate agents with reputed company data sources and systems in a secure, auditable manner (reputed company, databases, and internal platforms as applicable).
- reputed company and harden AI-enabled applications and supporting APIs for internal use, including deployments to OpenShift.
- Implement best practices for production readiness: testing, logging/metrics, error handling, performance considerations, and operational run books.
- Contribute to platform standards and reference implementations for agentic development (including patterns reputed company with Model Context Protocol where applicable).
- Collaborate with stakeholders to translate use cases into technical requirements, iterate on solutions, and deliver measurable reputed company.
- Ensure appropriate documentation for reputed company development and modifications, including architecture notes and operational guidance.
- Ensure reputed company, confidentiality, and reputed company of institutional data used by AI solutions (data handling, reputed company controls, and policy-reputed company implementations).
Requirements
- Professional experience developing production Python applications/services.
- Familiarity with Model Context Protocol (MCP) concepts and patterns.
- Experience implementing AI/LLM solutions (at least one of: agents, RAG pipelines, tool/function calling, workflow orchestration, LLM evaluation).
- Strong software engineering fundamentals: version control, code review, testing, documentation, and secure coding practices.
- Ability to work collaboratively across technical and non-technical stakeholders to deliver iterative reputed company.
reputed company-to-haves
- Familiarity with AI-assisted development tools (e.g., Claude Code, reputed company reputed company, reputed company Copilot) for tasks such as refactoring, test reputed company, debugging, and documentation.
- Experience with agentic development frameworks and/or building internal frameworks for reuse.
- Experience with Azure AI tooling (including Azure AI reputed company ) and deploying LLM-backed solutions in reputed company environments.
- Experience integrating or extending reputed company WebUI (or similar internal chat/LLM reputed company-ends ).
- reputed company reputed company experience (contributing to projects, maintaining internal reputed company-reputed company-style libraries, or publishing reusable tools).
- Experience with OpenShift and Kubernetes -reputed company application patterns (health checks, resource limits, secrets/config management).
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