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Senior AI Engineer

Job in Virginia, St. Louis County, Minnesota, 55792, USA
Listing for: Zenius Corporation
Full Time position
Listed on 2026-06-02
Job specializations:
  • Software Development
    AI Engineer, Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 100000 - 125000 USD Yearly USD 100000.00 125000.00 YEAR
Job Description & How to Apply Below

We are searching for an AI Product expert who can take ownership of a SaaS product and work with frontend and backend engineers to release world class AI product offerings. This is a hands‑on leader with coding experience and with deep experience in AI technologies, GPUs, Multi-agent frameworks, AI models and knows a lot about inference, fine tuning, agents, optimization quantization, etc.

Salary: Depends On Experience And Current Verifiable (paychecks) Compensation.

Location: Northern Virginia

Summary Of

The Role

We're looking for a Senior AI Product Manager / Engineer to design and build end-to-end AI systems - from model deployment and optimization to autonomous agent orchestration. This is not a research-only role. You'll operate at the intersection of:

  • LLMs & multimodal models
  • agent frameworks and workflow orchestration
  • production-grade infrastructure

You will help define how intelligent systems are built, deployed, and scaled in real‑world environments.

What You'll Work On
  • Design and implement autonomous AI agents capable of multi‑step reasoning, tool use, and workflow execution
  • Build agent orchestration systems (memory, planning, tool calling, state management)
  • Deploy and serve models (LLMs, vision, multimodal) in production environments
  • Optimize models via fine‑tuning (LoRA, full fine‑tune), quantization (INT8, 4‑bit, GGUF, etc.), distillation and performance tuning
  • Develop multi-model pipelines (generation + retrieval + tools + agents)
  • Integrate external tools/APIs into agent workflows
  • Build evaluation systems for reasoning quality, hallucination detection, task success rates
Core Responsibilities AI / ML Systems
  • Architect and implement end-to-end AI pipelines
  • Work with open‑source and proprietary models (LLMs, diffusion, etc.)
  • Implement RAG systems, embeddings, and vector search
  • Design prompting + system instruction strategies
  • Improve latency, throughput, and cost efficiency
Infrastructure & Deployment
  • Deploy models using modern stacks (containers, GPUs, serverless where applicable)
  • Build scalable inference systems
  • Manage model versioning, monitoring, and rollback strategies
  • Work with distributed systems and async processing pipelines
Agent & Workflow Engineering
  • Build custom agent frameworks or extend existing ones
  • Implement planning/reasoning loops, tool usage, memory (short‑term + long‑term)
  • Design reusable workflows for real‑world use cases
Software Engineering Excellence
  • Write clean, maintainable, production‑grade code (Python primarily)
  • Design APIs and services for internal and external use
  • Collaborate with product and design to ship user‑facing features
Process & Engineering Rigor
  • Write clear technical requirements (PRDs / tech specs)
  • Produce and maintain technical documentation
  • Conduct code reviews and enforce engineering standards
  • Define evaluation metrics and testing strategies for AI systems
  • Participate in architecture discussions and system design
Requirements Must‑Have
  • 3-5+ years in software engineering, with a strong focus on AI/ML systems
  • Hands‑on experience with LLMs and/or multimodal models
  • Experience building or working with AI agents or multi‑step workflows
  • Strong Python skills and familiarity with ML frameworks (PyTorch, etc.)
  • Experience with model deployment (Docker, cloud, GPU infra), fine‑tuning, and/or quantization
  • Solid understanding of prompt engineering, RAG architectures, embeddings + vector databases
Nice‑to‑Have
  • Experience with frameworks like Lang Graph, Lang Chain, Llama Index or custom agent systems
  • Familiarity with model serving tools (vLLM, Tensor

    RT, ONNX, etc.)
  • Experience with distributed systems and high‑scale APIs
  • Background in performance optimization/systems engineering
  • Contributions to open‑source AI projects
What We Value
  • Builders who ship, not just experiment
  • Strong systems thinking (not just model‑level thinking)
  • Ability to move between research ideas and production systems
  • Clear communication and documentation habits
  • Ownership mindset and product intuition
Why This Role
  • Work on cutting‑edge agent systems, not just wrappers
  • High ownership and ability to shape architecture
  • Build a full‑stack AI platform, not a narrow feature
  • Fast‑moving environment with real‑world impact
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Position Requirements
10+ Years work experience
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