Job Description
We are seeking a Solutions Engineer – Agentic AI & Model Optimization for a Full-Time role based in the California. Our client is a well-capitalized, next-generation enterprise technology provider purpose-building advanced AI software systems, autonomous agent factories, and scalable inference/training optimization pipelines. Their engineering platform enables enterprise customers to build, fine-tune, optimize, and deploy high-impact AI workloads and multi-agent workflows into secure production environments.
This is a premier opportunity to serve as the leading technical voice at the frontier of applied enterprise artificial intelligence. The #1 feature of this opportunity is the opportunity to deploy advanced model architectures and agentic frameworks backed by world-scale dedicated compute: you will partner with commercial leadership to architect autonomous agent systems, run model optimization evaluations, and demonstrate enterprise feasibility to Chief AI Officers and engineering leadership. We are seeking a researcher-grade or senior systems technologist with deep foundational AI knowledge (dating beyond recent trends) who combines hands-on engineering depth with consultative, customer-facing polish and leadership ambition. In exchange, you will work on state-of-the-art problems with massive computing support in a high-autonomy, growth-focused culture.
Required Skills & Experience
- 5+ years of combined experience in applied AI engineering, systems engineering, or technical pre-sales/solutions architecture with enterprise customers.
- Deep theoretical and practical knowledge of model architectures, transformer fundamentals, model fine-tuning, and inference/training optimization techniques (e.g., quantization, model parallelism, memory optimization).
- Hands-on experience designing or deploying autonomous agent frameworks, multi-agent orchestration, tool use, and structured workflow automation.
- Strong programming proficiency in Python and modern deep learning frameworks (PyTorch, Hugging Face, TensorRT-LLM, vLLM, or equivalent runtimes).
- Demonstrated customer-facing acumen with the ability to run technical discovery, design proofs-of-value (PoVs), and effectively present complex AI concepts to executive and research audiences.
Desired Skills & Experience
- Academic or commercial research background in machine learning, natural language processing, or autonomous systems prior to recent generative AI cycles.
- Experience addressing enterprise concerns around data privacy, secure model inference, deterministic agent behavior, and evaluation benchmarks.
- Prior experience at an AI-native startup, enterprise AI software vendor, or frontier applied AI organization.
- Master’s or Ph.D. in Computer Science, Machine Learning, Computational Mathematics, or related field, or equivalent practical experience.
What You Will Be Doing
Tech Breakdown
- 40% Agentic AI Systems, Multi-Agent Orchestration & Workflow Design
- 35% Inference & Training Optimization (Quantization, Runtimes, Model Serving)
- 25% Applied Model Development, Evaluation & Tool Integration
Daily Responsibilities
- 45% Customer Architecture Discovery, PoV Scoping & Executive Briefings
- 35% Hands-On Technical Solution Design, Prototype Validation & Technical Proposals
- 20% Team Collaboration & Research/Product Roadmap Alignment
The Offer
- Commission eligible
You Will Receive The Following Benefits
- Medical Insurance
- Dental Benefits
- Vision Benefits
- Paid Time Off (PTO)
Applicants must be currently authorized to work in the US on a full-time basis now and in the future.
Posted By: Adam Carman