Engineering · Remote

Forward Deployed Engineer

The Role

As a Forward Deployed Engineer, you’ll work at the intersection of engineering, AI, product, and customer success. You’ll partner directly with enterprise customers to deploy Quaeris into complex data environments, build integrations, solve technical challenges, and ensure customers realize measurable business value.

This is not a traditional implementation or solutions engineering role. You’ll write production-quality code, design scalable architectures, and serve as the technical bridge between customer requirements and our product roadmap.

What You’ll Do

  • Lead technical deployments for enterprise customers from kickoff through production.
  • Integrate Quaeris with customer data platforms including Snowflake, Databricks, BigQuery, Amazon Redshift, and Microsoft Synapse.
  • Build APIs, connectors, automation workflows, and custom integrations.
  • Configure authentication, access control, governance, and security requirements.
  • Design and implement AI-powered workflows using LLMs, RAG, semantic search, and enterprise data.
  • Debug complex customer environments and resolve production issues quickly.
  • Collaborate closely with Product and Engineering to convert customer feedback into platform improvements.
  • Create reusable deployment frameworks, templates, documentation, and tooling.
  • Conduct architecture workshops and technical discovery sessions with customer engineering and data teams.
  • Become a trusted technical advisor throughout the customer journey.

What We’re Looking For

Required Qualifications

  • 3+ years of software engineering or solutions engineering experience.
  • Strong proficiency in Python, C#, Java, or similar backend languages.
  • Experience designing and consuming REST APIs.
  • Strong SQL skills and experience working with modern cloud data warehouses.
  • Familiarity with cloud platforms (AWS, Azure, or GCP).
  • Experience integrating enterprise SaaS applications and APIs.
  • Excellent troubleshooting and debugging skills.
  • Strong communication skills with both technical and business stakeholders.
  • Ability to manage multiple customer engagements simultaneously.

Preferred Qualifications

  • Experience building AI or LLM-powered applications.
  • Knowledge of Retrieval-Augmented Generation (RAG), vector databases, or agentic AI.
  • Experience with Docker, Kubernetes, Terraform, or cloud infrastructure.
  • Familiarity with data governance, semantic layers, RBAC, and enterprise security.
  • Experience working with BI or analytics platforms.
  • Customer-facing consulting or implementation experience in enterprise software.

What Success Looks Like

Within your first year, you will:

  • Successfully deploy Quaeris across multiple enterprise environments.
  • Reduce customer time-to-value through reusable deployment patterns.
  • Build integrations that become part of the core platform.
  • Influence product direction through customer insights.
  • Become a trusted technical partner for strategic accounts.

Why Join Quaeris?

  • Build AI products that solve real enterprise problems.
  • Work with cutting-edge agentic AI and modern data platforms.
  • Partner directly with customers solving complex analytics challenges.
  • Influence product strategy through real-world deployments.
  • Join a team focused on secure, governed, enterprise-grade AI from day one.

Technologies You’ll Work With

  • Python, C#, .NET
  • SQL
  • Snowflake, Databricks, BigQuery, Redshift, Synapse
  • REST APIs
  • Docker & Kubernetes
  • Azure, AWS, GCP
  • LLMs and AI Agents
  • RAG & Vector Search
  • Git & CI/CD

If you enjoy solving difficult technical problems, working directly with enterprise customers, and shipping production AI systems that deliver measurable impact, we’d love to hear from you.

Apply for this role