Job Summary
Forward Deployed Engineer (FDE)
Role Overview
We are looking for a Forward Deployed Engineer to work directly with customers and engineering teams to identify high-value business problems and build, deploy, and productionize AI-powered solutions.
The FDE operates at the intersection of AI, software engineering, solution architecture, and customer problem-solving, taking solutions from initial discovery and rapid prototyping through production deployment and adoption.
Key Responsibilities
Key Responsibilities
· Work directly with customers and domain experts to understand business problems and identify high-impact AI use cases.
· Translate business requirements into practical AI/technical solutions.
· Rapidly prototype AI applications, agents, RAG systems, and workflow automations.
· Design and implement integrations with customer APIs, databases, enterprise systems, and existing applications.
· Build production-quality software using modern programming languages, APIs, cloud platforms, and AI/LLM technologies.
· Evaluate AI solutions for accuracy, reliability, latency, cost, and business impact.
· Troubleshoot real-world deployment challenges and iterate on solutions quickly.
· Collaborate with AI Architects, Product, Research, Security, and Engineering teams.
· Take ownership of deployments from discovery → prototype → production → handoff.
· Capture learnings from customer deployments and help turn them into reusable products, patterns, and platform capabilities.
Experience
· 6-10 years of professional software engineering experience, with strong backend, full-stack, platform engineering, or solution delivery experience.
· 2+ years of hands-on experience building AI/GenAI solutions using LLMs, RAG, AI Agents, or enterprise AI platforms.
· Experience designing, deploying, and supporting production applications in enterprise environments.
· Experience working directly with customers, business users, or stakeholder-facing project teams
Skill Requirements
Required Skills
Technical
· Strong software engineering and programming fundamentals.
· Experience building production applications and integrating APIs.
· Good understanding of LLMs, prompt engineering, RAG, embeddings, vector databases, and AI agents.
· Familiarity with cloud platforms, databases, authentication, security, and enterprise integrations.
· Ability to debug and solve complex technical problems independently.
· Understanding of AI evaluation, observability, guardrails, and production reliability.
· Hands-on experience with Azure, AWS, or GCP cloud platforms.
· Experience with Docker, Kubernetes, CI/CD, and cloud-native deployment practices.
· Knowledge of LLMOps including monitoring, evaluation, tracing, prompt/model versioning, latency optimization, and cost management.
· Experience with SQL/NoSQL databases, ETL pipelines, message queues, streaming systems, and enterprise data integration.
· Familiarity with authentication, security, governance, and enterprise integration patterns.
· Ability to debug and solve complex technical problems independently.
· Understanding of AI evaluation, observability, guardrails, and production reliability.
Problem Solving
· Ability to work with ambiguous requirements.
· Strong analytical and troubleshooting skills.
· Ability to quickly prototype and validate ideas.
· Customer and business-oriented thinking.
Collaboration
· Excellent communication and stakeholder-management skills.
· Comfortable working directly with customers and senior business/technical stakeholders.
· Ability to explain complex AI concepts in simple business terms.
· Ability to collaborate across Architecture, Engineering, Product, Research, Security, and Sales/GTM teams.
Other Requirements
Good Communication Skills