Senior AI Engineer (Python)
J
JobgetherEnterprise AI
Work remotely from IndiaFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- At least 8 years of hands-on experience in Python development and enterprise application engineering; at least 2 years of practical experience with LangGraph; at least 2 years of experience with LangChain.
- Required Skills
- PythonRESTful APIsGenerative AILangChain
Requirements
- At least 8 years of hands-on experience in Python development and enterprise application engineering.
- At least 2 years of practical experience with LangGraph, including agent workflows, stateful orchestration, multi-agent systems, and AI-driven execution flows.
- At least 2 years of experience with LangChain, including LLM-powered applications, tool integrations, retrieval-augmented generation (RAG), and workflow automation.
- Strong understanding of agentic AI concepts, including intelligent agents, planning, orchestration, memory management, and tool-calling frameworks.
- Experience building, deploying, and maintaining production-grade generative AI applications.
- Experience integrating AI solutions with enterprise platforms, backend services, and APIs.
- Practical experience designing and delivering production conversational AI and chat-based applications.
- Familiarity with AI observability, monitoring, telemetry, model evaluation, and performance analysis tools.
- Strong knowledge of software engineering principles, automated testing, debugging, code quality, and performance optimization.
- Experience working in Agile development environments and collaborating with cross-functional teams.
- Hands-on experience with Model Context Protocol (MCP) and Agent-to-Agent (A2A) communication is a nice-to-have.
- Knowledge of RAG architectures, enterprise knowledge systems, vector databases, and semantic search technologies is a nice-to-have.
Responsibilities
- Develop, enhance, and maintain AI agents and orchestration capabilities using Python, LangGraph, and LangChain.
- Build AI-enabled guided workflows, intelligent automation solutions, and enterprise AI capabilities.
- Design, implement, and optimize conversational AI applications and chat-based user experiences.
- Develop agent planning, state management, orchestration, memory, tool-calling, and response-generation capabilities.
- Integrate AI agents and applications with enterprise platforms, backend services, APIs, and external tools.
- Implement AI observability, monitoring, telemetry, evaluation, and performance-tracking capabilities.
- Collaborate with engineering teams and business stakeholders to define technical approaches and deliver AI-powered business use cases.
- Troubleshoot technical issues, strengthen application reliability, and optimize system performance.
- Contribute to architecture discussions, engineering standards, reusable components, testing practices, and scalable AI development methodologies.
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