Senior Forward Deployed Engineer (Agentic AI, RAG, Enterprise Architecture)

Candidate must be in Texas - will work remotely - as the role requires up to 25% travel for customer engagements.


Must Haves:
Multi-agent orchestration, LLM, RAG workflows, SLM fine-tuning, Python, Docker, Kubernetes, CI/CD, GraphQL

Job Description:
A fast-growing enterprise AI company is looking for a Senior Forward Deployed Engineer to take technical ownership of strategic AI solution deployments for enterprise customers. This role combines hands-on engineering, solution architecture, customer partnership, and delivery leadership, with a focus on building customer-specific applications on an Agentic AI platform.

You will lead the architecture, prototyping, implementation, and post-deployment optimization of large-scale Agentic and Knowledge AI solutions. The role involves working across enterprise data pipelines, multi-agent orchestration, RAG workflows, SLM fine-tuning, platform customization, full-stack delivery, and production-grade AI systems. You will collaborate closely with customers, Product, Platform Engineering, and cross-functional teams to translate ambiguous business needs into scalable engineering plans and successful deployments.

Required Skills
10+ years of engineering experience, including at least 2 years in customer-facing, field engineering, solutions engineering, or forward deployed engineering roles
Proven experience building and deploying AI/ML, data-intensive, or enterprise-grade applications in production
Strong full-stack development experience with Python, Node.js or Go, and React or Vue
DevOps experience with Docker, Kubernetes, CI/CD, and modern cloud-based deployment practices
Experience designing and implementing enterprise data pipelines and system integrations
Strong knowledge of REST APIs, Python, SQL, GraphQL, Webhooks, and enterprise integration patterns
Solid understanding of LLMs, prompt engineering, prompt tuning, vector databases, RAG pipelines, and agentic workflows
Experience with vector databases such as AstraDB, Pinecone, or Weaviate
Familiarity with RAG frameworks such as LlamaIndex or Haystack
Experience with agent and workflow orchestration tools such as LangChain, LangGraph, or CrewAI
Ability to lead technical solution design and implementation for strategic enterprise customers
Experience customizing platform components, integrating APIs, building reusable tooling, or extending platform logic
Strong understanding of observability, monitoring, versioning, telemetry, and trustworthy AI deployment practices
Ability to translate ambiguous customer needs into clear, actionable engineering plans
Strong project ownership, mentoring, communication, and collaboration skills across technical and business stakeholders
Undergraduate degree, master’s degree, or PhD in Computer Science, Data Science, or a related technical field.

Bonus Skills
Knowledge of SLM fine-tuning, model distillation, and model optimization techniques
Experience building and delivering enterprise Agentic AI solutions
Experience working with Agentic development platforms
Familiarity with graph databases, multimodal AI systems, evaluation frameworks, security, guardrails, and GPU infrastructure trends
Experience contributing to reusable assets, technical best practices, internal frameworks, and documentation
Prior experience supporting post-deployment optimization and production adoption for enterprise customers
Experience partnering with Product and Platform Engineering teams to identify feature gaps, customer pain points, and product improvement opportunities.