AI Software Engineer

Your Impact As a Software Engineer, you will design and implement AI-driven features and autonomous agents within the Partner Hub. You will bridge the gap between AI Frameworks, complex AI models, and practical, scalable production systems. Your work will directly empower our partners by automating complex workflows, providing predictive insights, and creating a more intuitive, conversational platform experience. You will act as a technical subject matter expert, mentoring junior team members on AI best practices and ensuring our systems are robust, secure, and highly performant. Key Responsibilities Design and develop autonomous agents and AI-driven workflows that integrate seamlessly into the Partner Hub ecosystem. Implement scalable solutions using Large Language Models (LLMs), vector databases, and agentic frameworks (e.g., LangChain, or similar). Establish standards for model evaluation, prompt engineering, and agentic reliability. Provide high-level technical guidance and mentorship to junior engineering team, fostering a culture of innovation in AI and machine learning. Ensure AI features are production-ready, focusing on latency, cost-efficiency, security, and ethical AI practices. Partner with product management and data science teams to translate business needs into cutting-edge AI solutions. Stay at the cutting edge of the AI/Agentic landscape, evaluating and integrating new frameworks and tools to maintain our competitive advantage. Minimum Qualifications Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field. Extensive professional experience in software engineering with a strong focus on AI/ML and agentic systems. Proven track record of deploying AI-powered applications into production environments at scale. Proficiency in Python or Java, with deep experience in AI frameworks and LLM orchestration. Strong understanding of distributed systems, API design, and cloud-native architectures. Preferred Qualifications Hands-on experience with agentic frameworks (e.g., LangChain, CrewAI, AutoGen) and multi-agent orchestration. Experience integrating AI with streaming/batch data platforms (e.g., Spark, Flink, or vector databases like Pinecone/Milvus). Experience with fine-tuning, RAG (Retrieval-Augmented Generation), and LLM observability/evaluation tools. Extensive experience architecting AI solutions within major cloud environments (AWS, GCP, or Azure). Significant experience managing the full lifecycle of mission-critical, high-availability AI platforms. Demonstrated history of leading technical initiatives and mentoring engineering teams. Exceptional strategic thinking, communication, and stakeholder management skills.