Senior Python AI Engineer

We are delivering production-ready AI capabilities in Python by building multi-agent systems, RAG pipelines, and safe guardrails that create real business impact. You will drive MCP integrations, orchestrate agents with LangChain, LangGraph, and CrewAI, and connect models through AWS Bedrock and GCP Vertex AI with strong observability and security. Apply today to help us ship reliable, scalable AI solutions.

Responsibilities

• Architect and implement scalable systems to power data-driven intelligent applications
• Translate complex technical ideas into working systems that support company objectives
• Collaborate with cross-functional partners to define technical requirements and deliver high-quality outcomes
• Create clear, maintainable code following industry practices and backed by thorough documentation
• Identify and solve technical issues across each stage of the software development lifecycle
• Contribute to peer code reviews and share actionable feedback that improves team output
• Investigate new technology trends and recommend upgrades for the existing infrastructure
• Participate in architectural decision-making that shapes future technical direction
• Mentor junior colleagues and distribute technical knowledge across the wider team
• Ensure solutions prioritize scalability, performance, and long-term maintainability

Requirements

• Demonstrated 3+ years of applied Python engineering experience, including developing, deploying, and operating reliable AI systems and intelligent applications in production settings
• Deep expertise in implementing stateful multi-agent processes, autonomous agentic systems, and multi-agent orchestration using LangChain, LangGraph, CrewAI, Google ADK, and AWS Strands Agents SDK
• Direct, real-world experience with Model Context Protocol (MCP) integration
• Proven experience developing and sustaining Retrieval-Augmented Generation (RAG) pipeline systems
• Strong practical skills in prompt engineering to improve language model communication
• Experience building guardrail mechanisms that keep AI systems safe and behavior controlled
• Knowledge of knowledge graphs and their application within AI solutions
• Hands-on experience integrating foundation models using cloud services such as AWS Bedrock and GCP Vertex AI
• Ability to maintain strong evaluation methods, observability, and security controls across live AI deployments
• Effective communication skills and functional English proficiency (B2 level or above) to understand business needs and turn them into agentic architecture designs