Note: The job is a remote job and is open to candidates in USA. Dice is seeking a highly skilled Forward Deployed Engineer to support SingleStore customers globally. The role focuses on deploying and optimizing SingleStore database environments, implementing AI-powered Aura Analyst solutions, providing technical consulting, and serving as a trusted customer advisor throughout the implementation lifecycle.
Responsibilities
- Deploy, configure, and optimize SingleStore Helios environments for enterprise customers
- Install, configure, and support Self-Managed SingleStore clusters across cloud and on-premises infrastructure
- Perform cluster sizing, architecture design, upgrades, migrations, and production readiness assessments
- Configure high availability, disaster recovery, backup, security, and performance optimization
- Troubleshoot complex infrastructure, database, and deployment issues
- Deploy and configure Aura Analyst for enterprise customers
- Integrate Aura Analyst with customer datasets and enterprise workflows
- Enable customers to leverage natural language queries and AI-powered analytics
- Validate AI outputs, optimize prompts, and support customer adoption
- Collaborate with SingleStore Product and Engineering teams by providing implementation feedback and product improvement recommendations
- Serve as the primary technical advisor during customer implementations
- Lead discovery sessions, technical workshops, and architecture reviews
- Translate business objectives into scalable technical solutions
- Recommend best practices for deployment, performance, scalability, and security
- Produce high-quality technical documentation and implementation guides
- Leverage AI tools to accelerate deployments, troubleshooting, documentation, and knowledge sharing
- Develop automation scripts to simplify repetitive deployment and operational tasks
- Utilize modern AI coding assistants and productivity tools to improve engineering efficiency
- Stay current with advancements in Large Language Models (LLMs), AI agents, and enterprise AI technologies
- Build trusted relationships with customer stakeholders, architects, and engineering teams
- Drive successful implementations while ensuring an exceptional customer experience
- Mentor customer teams through knowledge transfer sessions and operational best practices
- Collaborate with Customer Success and Support teams to ensure seamless project handoffs
Skills
- Bachelor's degree in Computer Science, Information Technology, Engineering, or
- Equivalent practical experience
- 8+ years of experience in Professional Services, Solutions Engineering, Customer Engineering, Forward Deployed Engineering, or Technical Consulting
- Experience deploying enterprise software solutions in customer environments
- Experience with SingleStore or distributed SQL databases such as PostgreSQL, CockroachDB, YugabyteDB, MySQL, or similar technologies
- Database administration and performance tuning experience
- Data ingestion and ETL pipelines
- Monitoring platforms such as Grafana, Prometheus, or Datadog
- Infrastructure as Code using Terraform or Ansible
- CI/CD pipelines and DevOps practices
- Strong Linux system administration skills
- Experience with AWS, Microsoft Azure, or Google Cloud Platform
- Hands-on experience with Kubernetes and containerized applications
- Strong networking fundamentals, including DNS, TLS/SSL, firewalls, and load balancing
- Experience with Python, Bash, or other scripting languages
- Familiarity with REST APIs and enterprise integrations
- Excellent troubleshooting and analytical skills
- Exceptional verbal and written communication skills
- Strong presentation and executive communication capabilities
- Excellent consulting and stakeholder management skills
- Ability to simplify complex technical concepts for both technical and non-technical audiences
- Strong business acumen and customer-first mindset
- Experience leading customer workshops and architecture discussions
- Excellent problem-solving and analytical thinking skills
- Ability to manage multiple customer engagements simultaneously
- Hands-on use of AI tools such as ChatGPT, Claude, Gemini, GitHub Copilot, Cursor, Windsurf, or similar platforms
- Knowledge of Model Context Protocol (MCP) and its role in enabling AI assistants to securely interact with enterprise databases, APIs, development tools, and business applications
- Using AI to improve implementation quality, scripting, troubleshooting, documentation, and customer enablement
- Large Language Models (LLMs)
- Prompt Engineering
- Retrieval-Augmented Generation (RAG)
- AI Agents and MCP (Model Context Protocol)
- Vector Databases and Embeddings
- Experience implementing AI-powered enterprise applications is highly desirable
- Experience delivering Professional Services engagements
- Exposure to enterprise analytics platforms
- Cloud certifications (AWS, Azure, or Google Cloud Platform)
- Kubernetes certification is a plus
- Experience supporting Fortune 500 or enterprise customers
Benefits
- Remote work arrangement
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