Senior Forward Deployed Engineer, Agentic AI & RAG

About the Role\n

Lead the architecture and delivery of production Agentic AI and enterprise knowledge solutions for strategic customers. This role combines hands-on engineering, solution architecture, customer partnership, and delivery leadership across complex enterprise environments.

\n

This is a remote U.S. contract role. Texas-based candidates are preferred, and the work requires up to 25% travel for customer engagements.

What You'll Do\n

\n
• Translate ambiguous customer needs into scalable technical plans and successful AI deployments.
\n
• Architect, prototype, implement, and optimize customer-specific applications on an Agentic AI platform.
\n
• Build enterprise data pipelines, system integrations, multi-agent orchestration, RAG workflows, platform extensions, and production-grade AI services.
\n
• Lead technical solution design with customers and partner closely with Product, Platform Engineering, and other cross-functional teams.
\n
• Improve post-deployment reliability, observability, performance, adoption, and reusable delivery practices.
\n

Requirements\n

\n
• 6+ years of engineering experience, including at least 2 years in customer-facing, field engineering, solutions engineering, or forward-deployed engineering roles.
\n
• Proven experience building and deploying production AI/ML, data-intensive, or enterprise-grade applications.
\n
• Strong full-stack development experience with Python, Node.js or Go, and React or Vue.
\n
• Hands-on DevOps experience with Docker, Kubernetes, CI/CD, and cloud-based deployment practices.
\n
• Experience designing enterprise data pipelines, system integrations, REST APIs, SQL, GraphQL, webhooks, and reusable platform tooling.
\n
• Strong knowledge of LLMs, prompt engineering and tuning, vector databases, RAG pipelines, and agentic workflows. Relevant tools may include Pinecone, Weaviate, AstraDB, LlamaIndex, Haystack, LangChain, LangGraph, or CrewAI.
\n
• Ability to lead strategic customer implementations, translate uncertain business needs into actionable plans, and communicate effectively across technical and business stakeholders.
\n
• An undergraduate, master's, or PhD degree in Computer Science, Data Science, or a related technical field.
\n

Preferred Experience\n

\n
• SLM fine-tuning, model distillation, or model optimization.
\n
• Enterprise Agentic AI delivery, graph databases, multimodal AI, evaluation frameworks, security and guardrails, or GPU infrastructure.
\n
• Production observability, monitoring, versioning, telemetry, trustworthy AI practices, and post-deployment optimization.
\n
• Creating reusable technical assets, internal frameworks, documentation, or platform improvements.
\n

Engagement and Selection\n

This is a full-time contract requiring 40 hours per week during Central Time business hours, with full working-hours overlap. The engagement is expected to begin as soon as possible and continue for at least six months. The selection process includes an initial HR screen, a technical screen, and two client interview rounds.

Compensation\n

$63-$84 USD per hour.