Senior Software Engineer – Applied AI

Senior Software Engineer – Applied AI

Requirements

• Strong Python Proficiency: Solid Python skills including async programming, testing practices, and familiarity with AI/ML libraries like OpenAI SDK, Anthropic SDK, or similar. Experience with prompt engineering and model integration.
• Agent Framework Experience: Hands-on experience with at least one major agent orchestration framework (LangGraph, LangChain, CrewAI, AutoGen) and understanding of agent workflow patterns and best practices.
• RAG Implementation Skills: Experience building retrieval-augmented generation systems, including vector database usage (Pinecone, Weaviate, Chroma), embedding strategies, and optimizing retrieval accuracy.
• MCP Server Development: Experience building Model Context Protocol (MCP) servers or similar agent integration patterns. Understanding of protocol specifications and resource management.
• Distributed Systems Architecture: Experience designing scalable, fault-tolerant agent systems using microservices, event-driven patterns, and proper state management.
• Cloud and Deployment: Proficiency with containerization (Docker) and cloud platforms (AWS, GCP, Azure). Experience with CI/CD pipelines and production deployment practices.
• Testing and Evaluation: Experience implementing testing strategies for AI systems, including unit testing, integration testing, and basic evaluation metrics for model performance.
• System Integration: Ability to integrate AI agents with databases, APIs, and enterprise systems. Understanding of authentication, error handling, and data privacy considerations.
• Communication Skills: Strong written and verbal communication skills, with ability to explain technical concepts to both technical and non-technical stakeholders.
• Collaborative Mindset: Proven ability to work effectively in cross-functional teams, contribute to code reviews, and participate in technical discussions and planning sessions.
• Continuous Learning: Demonstrated interest in staying current with rapidly evolving AI technologies and frameworks. Experience with open source contributions or personal AI projects is a plus.
• OSS Experience: Experience contributing to or maintaining open source software projects, with demonstrated ability to collaborate in distributed development environments
• Startup Mindset: Self-motivated and hands-on. Thrives in dynamic, fast-changing environments and drives clarity through action.

Responsibilities

• Build and Optimize AI Agents: Develop production-quality AI agents and tools that solve specific business problems, focusing on reliability, performance, and user experience. Collaborate with senior engineers on architectural decisions and implementation approaches.
• Implement Agent Orchestration: Work with frameworks like LangGraph, LangChain, or CrewAI to build robust agent workflows, handling complex multi-step processes and integrations with external systems.
• Develop RAG Solutions: Build and maintain retrieval-augmented generation pipelines, including vector database integration, embedding optimization, and retrieval strategy implementation.
• Collaborate on Technical Discovery: Partner with product managers and senior engineers to understand customer needs, prototype solutions, and validate technical approaches for new agent capabilities.
• Ensure Production Quality: Implement comprehensive testing, monitoring, and error handling for AI systems. Contribute to deployment processes and operational excellence practices.
• Share Knowledge and Mentor: Guide junior engineers in AI agent development practices, code review best practices, and technical problem-solving approaches.
• Drive Technical Innovation: Evaluate new AI tools, frameworks, and techniques to improve development velocity and solution quality. Contribute to engineering standards and best practices.
• Champion AI-First Engineering: Use AI tools and workflows to streamline development, inform decisions, and accelerate innovation in how software is built and delivered.

Preferred Qualifications

• Strong Python Proficiency: Solid Python skills including async programming, testing practices, and familiarity with AI/ML libraries like OpenAI SDK, Anthropic SDK, or similar. Experience with prompt engineering and model integration.
• Agent Framework Experience: Hands-on experience with at least one major agent orchestration framework (LangGraph, LangChain, CrewAI, AutoGen) and understanding of agent workflow patterns and best practices.
• RAG Implementation Skills: Experience building retrieval-augmented generation systems, including vector database usage (Pinecone, Weaviate, Chroma), embedding strategies, and optimizing retrieval accuracy.
• MCP Server Development: Experience building Model Context Protocol (MCP) servers or similar agent integration patterns. Understanding of protocol specifications and resource management.
• Distributed Systems Architecture: Experience designing scalable, fault-tolerant agent systems using microservices, event-driven patterns, and proper state management.
• Cloud and Deployment: Proficiency with containerization (Docker) and cloud platforms (AWS, GCP, Azure). Experience with CI/CD pipelines and production deployment practices.
• Testing and Evaluation: Experience implementing testing strategies for AI systems, including unit testing, integration testing, and basic evaluation metrics for model performance.
• System Integration: Ability to integrate AI agents with databases, APIs, and enterprise systems. Understanding of authentication, error handling, and data privacy considerations.
• Communication Skills: Strong written and verbal communication skills, with ability to explain technical concepts to both technical and non-technical stakeholders.
• Collaborative Mindset: Proven ability to work effectively in cross-functional teams, contribute to code reviews, and participate in technical discussions and planning sessions.
• Continuous Learning: Demonstrated interest in staying current with rapidly evolving AI technologies and frameworks. Experience with open source contributions or personal AI projects is a plus.
• OSS Experience: Experience contributing to or maintaining open source software projects, with demonstrated ability to collaborate in distributed development environments
• Communication: Excellent communication and collaboration skills, with the ability to work effectively across engineering, product, design, and business teams.
• Startup Mindset: Self-motivated and hands-on. Thrives in dynamic, fast-changing environments and drives clarity through action.