Senior GenAI Engineer

• Design, build, and deploy production-ready Generative AI and Agentic AI solutions for GTM business use cases.
• Build AI agents, copilots, and automation workflows to improve sales productivity, decision-making, and operational efficiency.
• Develop AI workflows that can retrieve trusted information, use tools, call APIs, reason over business context, and generate actionable recommendations.
• Build and maintain LLM-powered applications using Python and modern AI engineering practices.
• Implement Retrieval-Augmented Generation architectures using enterprise data, approved knowledge sources, vector search, and source-grounded responses.
• Develop prompts as managed, versioned, testable, and reusable engineering assets.
• Use agent and orchestration frameworks such as LangGraph, LangChain, LlamaIndex, Semantic Kernel, AutoGen, CrewAI, or similar technologies.
• Work with vector databases and search platforms such as Pinecone, Weaviate, FAISS, Milvus, Azure AI Search, OpenSearch, or similar technologies.
• Integrate AI applications with enterprise systems such as CRM, data warehouses, APIs, knowledge bases, collaboration tools, and GTM platforms.
• Build evaluation frameworks to test AI outputs for accuracy, groundedness, relevance, completeness, safety, and business usefulness.
• Implement monitoring and feedback loops to improve model performance, prompt quality, retrieval quality, cost, latency, and user experience.
• Design guardrails to reduce hallucinations, prevent unsafe outputs, protect sensitive data, and ensure responsible AI usage.
• Partner with IT, data engineering, architecture, security, and business teams to move AI solutions from prototype to production.
• Create reusable AI patterns, prompt libraries, evaluation templates, and implementation standards that can scale across multiple GTM AI use cases.
• Deliver trusted, secure, scalable, and useful AI solutions that improve productivity, decision-making, and business outcomes across the GTM organization.

To ensure you’re set up for success, you will bring the following skillset & experience:

• Bachelor’s degree in Computer Science, Engineering, Data Science, AI/ML, or a related technical field, or equivalent practical experience.
• 6+ years of experience in software engineering, data engineering, machine learning engineering, AI engineering, or related technical roles.
• 2+ years of hands-on experience building LLM, Generative AI, or Agentic AI applications.
• Strong programming experience in Python.
• Experience building production-grade applications, APIs, services, automation workflows, or data-driven solutions.
• Hands-on experience with LLM application development, prompt engineering, RAG architectures, vector search, tool use, and agent orchestration.
• Experience with AI frameworks such as LangGraph, LangChain, LlamaIndex, Semantic Kernel, AutoGen, CrewAI, or similar tools.
• Experience with enterprise AI platforms such as Microsoft Copilot Studio, Azure AI Foundry, Azure OpenAI, AWS Bedrock, Google Vertex AI, or similar platforms.
• Experience with vector databases or retrieval platforms such as Pinecone, Weaviate, FAISS, Milvus, Azure AI Search, OpenSearch, or similar technologies.
• Strong understanding of hallucination mitigation, grounding techniques, prompt injection risks, AI safety, guardrails, evaluation, and monitoring.
• Experience integrating AI solutions with APIs, databases, data warehouses, enterprise systems, and business applications.
• Ability to translate business problems into practical AI solution designs.
• Strong communication skills and ability to work effectively with both technical and non-technical stakeholders.
  • Hands-on builder mindset with the ability to move beyond demos and build enterprise-grade AI solutions that are grounded, tested, monitored, secure, and scalable.