Overview:Job Summary: The bottleneck in enterprise AI has moved from model access to deployment capability. R2 Technologies is seeking a Forward Deployed Engineer to work embedded with client teams-sitting with the people who will actually use the system, learning their workflow in detail, and shipping the integration code that makes AI work in their environment. This role combines hands-on engineering with direct client engagement, taking solutions from scoped requirement through production adoption.
Key Responsibilities:- Work embedded with client engineering and business teams to translate operational workflows into deployable AI solutions.
- Build and integrate LLM-powered applications and agents against client data sources, APIs, and legacy enterprise systems.
- Develop custom connectors, data pipelines, and integration layers required to make platform capabilities work in client-specific environments.
- Run discovery sessions with stakeholders, decompose ambiguous business problems into shippable scope, and set realistic delivery expectations.
- Own solutions through the full lifecycle-prototype, production deployment, monitoring, and iteration based on real user feedback.
- Document deployment patterns, integration decisions, and reusable components to accelerate subsequent client engagements.
Qualifications:- 3 years of experience in software engineering, solutions engineering, or applied AI deployment.
- Strong programming skills in Python, with working knowledge of TypeScript, Java, or Go.
- Hands-on experience integrating LLMs and building AI applications against enterprise data sources and APIs.
- Experience with REST APIs, microservices, authentication patterns, and enterprise system integration.
- Cloud deployment experience on AWS, Azure, or GCP, including containerization and CI/CD.
- Strong written and verbal communication; comfortable operating independently in client environments with ambiguous requirements.
Skills:Applied AI, LLM Integration, Python, Enterprise Integration, REST APIs, Client Engagement, Solution Deployment, RAG
