Forward Deployed Engineer

Job Description

About the Role

We're looking for a Senior Forward Deployed Engineer who can bridge the gap between advanced AI engineering and real-world business problems. You'll work directly with clients to design, build, and deploy agentic AI platforms that integrate into their existing systems and workflows. This isn't a role where you'll just build prototypes and hand them off. You'll own technical delivery, work closely with end users, and turn complex requirements into production-ready solutions. We need someone who understands how to build sophisticated AI systems, navigate enterprise environments, and deliver measurable outcomes.

What You'll Be Doing

• Design and build agentic AI platforms using Python and modern AI frameworks.
• Architect LLM orchestration systems using LangGraph, CrewAI, AutoGen, and related technologies.
• Develop multi-agent systems with tool use, workflow orchestration, memory, and decision-making capabilities.
• Design and deploy Retrieval-Augmented Generation (RAG) pipelines connected to enterprise data sources.
• Integrate AI platforms with client APIs, data platforms, cloud services, and enterprise applications.
• Configure Kubernetes environments and deploy production workloads.
• Design deployment architectures across cloud, on-premise, and hybrid environments.
• Work directly with clients and end users to understand requirements, solve technical challenges, and iterate on solutions.
• Collaborate with technical and non-technical stakeholders throughout client engagements.
• Take ownership of complex consulting engagements, from technical planning through execution and delivery.

What We're Looking For

• 3+ years of commercial software engineering experience, with a proven track record of delivering at Senior Engineer level.
• Strong hands-on experience with Python and modern AI development frameworks.
• Experience designing and building agentic platforms and LLM-powered applications.
• Deep understanding of LLM orchestration frameworks such as LangGraph, CrewAI, and AutoGen.
• Experience implementing multi-agent architectures, including tool calling, memory, and workflow management.
• Hands-on experience building and deploying RAG pipelines using enterprise data.
• Experience integrating complex systems through APIs, cloud services, and enterprise platforms.
• Practical knowledge of Kubernetes configuration and workload deployment.
• Experience designing cloud, on-premise, and hybrid deployment architectures.
• Strong consulting and client-facing experience, with the ability to translate business problems into technical solutions.
• Excellent communication and collaboration skills.
• Comfortable working in fast-moving environments where requirements evolve and solutions are refined through direct user feedback.

Why TEN-XER?

At TEN-XER, we believe great work starts with great people. We're focused on connecting exceptional talent with opportunities where they can make a meaningful impact. If you're someone who enjoys solving difficult engineering problems, working closely with clients, and taking AI systems from architecture to production, we'd like to hear from you.