Forward Deployed Engineer

We are seeking a Forward Deployed Engineer (FDE) who operates at the intersection of engineering, AI, product development, and enterprise customer engagement. In this role, you will collaborate directly with customers to understand complex business and technical challenges, rapidly develop and deploy AI-powered solutions, and integrate these technologies into real-world workflows. You will translate customer feedback into scalable product features, moving seamlessly from customer meetings to technical architecture, prototyping, and production deployment without relying on separate teams for each phase.

Key Responsibilities

- Work closely with enterprise customers to identify and understand their technical and business challenges.
- Translate ambiguous customer requirements into practical, production-ready technical solutions.
- Design, build, test, and deploy AI-powered applications and production-grade software.
- Rapidly develop prototypes and proof-of-concepts to validate new ideas.
- Integrate large language models (LLMs), AI agents, APIs, databases, and enterprise systems.
- Build integrations with platforms such as CRM, ERP, DevOps, cloud services, data, and collaboration tools.
- Deploy solutions into customer environments and troubleshoot production issues.
- Collaborate with product and engineering teams to transform recurring customer needs into core product features.
- Own the technical delivery lifecycle from discovery through deployment and adoption.
- Create reusable frameworks, integrations, and accelerators to reduce future deployment time.
- Participate in customer workshops, technical demonstrations, architecture discussions, and solution design sessions.
- Communicate complex technical concepts clearly to both engineering teams and senior business stakeholders.
- Identify opportunities to expand customer use cases and demonstrate additional product value.
- Build applications using modern AI/LLM technologies, including working with APIs, retrieval-augmented generation (RAG), vector databases, AI agents, tool calling, evaluation frameworks, and orchestration.
- Develop reliable AI workflows with appropriate monitoring, testing, security, and guardrails.
- Build APIs and backend services to operationalize AI solutions.
- Utilize cloud platforms and modern deployment practices.
- Understand software architecture, databases, authentication, APIs, microservices, and distributed systems.
- Rapidly evaluate emerging AI technologies to determine their potential for delivering meaningful customer value.

Required Qualifications

- 3 to 7+ years of professional experience in software engineering, solutions engineering, implementation engineering, or a similar technical role.
- Strong programming skills in Python, JavaScript/TypeScript, Java, Go, or comparable languages.
- Proven experience building and deploying production applications.
- Solid understanding of APIs, databases, cloud platforms, and software architecture.
- Experience working directly with customers or enterprise stakeholders.
- Strong problem-solving skills and ability to operate effectively with ambiguous requirements.
- Excellent communication and presentation skills.
- Ability to work independently and move quickly from concept to implementation.
- Deep understanding of modern AI/LLM capabilities and their limitations.

Preferred Qualifications and Benefits

- Experience building AI agents, RAG systems, copilots, or LLM-powered applications.
- Familiarity with AI APIs from providers such as OpenAI, Anthropic, Gemini, or others.
- Experience with cloud platforms like AWS, Azure, or Google Cloud Platform.
- Knowledge of Docker, Kubernetes, CI/CD pipelines, and modern DevOps practices.
- Experience integrating enterprise platforms such as Salesforce, ServiceNow, SAP, Microsoft, Jira, GitHub, or similar.
- Startup experience with a demonstrated ability to wear multiple hats.
- Experience working with Fortune 500 or large enterprise customers.
- Background in consulting, professional services, solutions architecture, or technical implementation.
- Proven track record of taking prototypes into production.

The ideal candidate is a builder who thrives on moving quickly from problem identification to prototype and production without waiting for perfect specifications. You are comfortable engaging with a range of stakeholders—from CTOs to engineers—while handling tasks such as writing code, designing APIs, configuring LLMs, debugging production issues, and presenting solutions to executives. Success in this role will be measured by the speed of delivering working solutions, customer satisfaction, quality and scalability of implementations, and your ability to create reusable capabilities that shorten deployment times and unlock new customer use cases.

This role offers a unique opportunity to work at the forefront of enterprise AI, solving real-world problems alongside customers rather than developing AI in isolation. You will gain significant ownership and exposure across AI, engineering, product, enterprise architecture, and customer strategy, with a direct influence on the future direction of the product.