Forward Deployed Solutions Engineer

Role Overview: You will be working as a Forward Deployed Solutions Engineer (FDSE) at XenonStack, directly engaging with enterprise customers to deploy and customize Agentic AI platforms for real-world impact. This hybrid role encompasses solutions engineering, consulting, and customer success, focusing on not just deploying agentic systems but also transforming business processes, decision-making, and workflows. Key Responsibilities: - Enterprise Deployment & Integration: - Deploy and configure Agentic AI, Vision AI, and Inference Infrastructure for enterprise clients. - Integrate solutions with enterprise APIs, data systems, and third-party tools. - Solution Engineering: - Translate client business requirements into technical architectures for agentic systems. - Customize AI agents and multi-agent workflows to align with industry-specific compliance and workflows. - Customer Collaboration: - Partner with CXOs, IT leaders, and domain experts to understand strategic challenges. - Conduct discovery sessions, demos, and workshops to showcase solution value. - Reliability & Observability: - Ensure deployments are reliable, observable, and cost-optimized. - Collaborate with AgentOps and Observability Engineers to monitor performance, traceability, and governance. - Feedback & Product Alignment: - Serve as the customers" technical voice within XenonStack. - Provide structured feedback to shape product features, roadmap, and UX improvements. - Training & Enablement: - Develop technical documentation, runbooks, and playbooks for clients. - Train customer teams on operating, monitoring, and scaling agentic systems. Qualifications Required: Must-Have: - 3-6 years of experience in Solutions Engineering, Forward-Deployed Engineering, or Enterprise SaaS delivery. - Strong proficiency in Python, APIs, and cloud-native platforms (AWS, GCP, Azure). - Familiarity with LLM orchestration frameworks (LangChain, LangGraph, LlamaIndex). - Hands-on experience with containerization (Docker, Kubernetes) and CI/CD pipelines. - Excellent communication and client-facing skills with the ability to engage senior stakeholders. - Proven ability to solve problems under pressure and adapt solutions to customer environments. Good-to-Have: - Experience with AgentOps tools (LangSmith, Arize AI, PromptLayer, Weights & Biases). - Knowledge of RAG pipelines, vector databases, and knowledge graph integration. - Background in deploying solutions for regulated industries (BFSI, GRC, SOC, Healthcare). - Understanding of Responsible AI practices (safety, fairness, compliance).,