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.
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