Omnis Partners
Artificial Intelligence Engineer (Dallas)
Omnis Partners, Dallas, Texas, United States, 75215
Forward Deployed Engineer - Agentic AI
Team Build: Multiple Hires
Dallas, Texas, United States - 3 days in office and local travel for client delivery Competitive salary + bonus + benefits Multiple Hires - Senior/Lead and Associate Director Level
Why This Role? This isnt just another AI position. Were looking for engineers who can architect and deliver agentic AI systems end-to-end, taking ideas well beyond prototypes into reliable, production-grade solutions. Youll collaborate closely with enterprise and public sector clients, guiding initiatives from early proof-of-concept through to business-critical platforms used by hundreds or even thousands of people.
What Youll Do Architect agentic systems:
Take ownership of the full agent lifecycle (plan
execute
learn), including orchestration via DAGs or state machines and long-term memory design. Develop resilient tooling:
Build schemas, retry logic, rate controls, and SDKs to enable safe and extensible system use. Design memory & knowledge layers:
Deliver episodic and semantic memory services, retrieval interfaces, deduplication pipelines, and summarisation agents. Ship to production at scale:
Roll out containerised platforms across Kubernetes, serverless environments, and GPU infrastructure, with CI/CD, monitoring, and automated scaling. Harden system reliability:
Implement guardrails, latency and cost controls, checkpointing, and reviewer/critic patterns to improve output quality. Run structured evaluation:
Create automated testing frameworks using golden datasets, retrieval performance checks, and ongoing drift detection. Partner with stakeholders:
Facilitate workshops, roadmap planning, and capability assessments, turning advanced AI concepts into clear, practical plans.
What Were Looking For Required: Demonstrated experience designing, building, and running LLM-powered or agentic systems in live production environments. Solid core engineering skills across orchestration, state and memory handling, deployment pipelines, and system observability. Working knowledge of agent-based patterns and frameworks (such as LangGraph, ReAct, or chain-of-thought loops), or the capability to implement these approaches from first principles. Comfortable operating in customer-facing contexts, including leading workshops, delivering presentations, and providing technical guidance or advisory support.
Preferred: Degree or higher in AI, Computer Science, or a related technical discipline. Familiarity with PyTorch or TensorFlow, vector databases, RAG workflows, and orchestration frameworks. Experience in start-ups (versatile, hands-on generalist) or consulting environments (client-facing). Exposure to regulated sectors or compliance-heavy industries. Self-driven, entrepreneurial attitude; able to work independently and take ownership of projects.
Why Join? Real-World Impact:
Build and deploy mission-critical agentic AI systems that solve tangible problems. Cutting-Edge Challenges:
Work on orchestration and deployment problems that go far beyond standard integration. Global Collaboration:
Remote-first role offering chances to work with teams around the world. Career Growth:
Shape enterprise AI strategies and contribute meaningfully to the wider AI ecosystem. Dynamic Culture:
Join a fast-moving team at the forefront of applied AI innovation.
Dallas, Texas, United States - 3 days in office and local travel for client delivery Competitive salary + bonus + benefits Multiple Hires - Senior/Lead and Associate Director Level
Why This Role? This isnt just another AI position. Were looking for engineers who can architect and deliver agentic AI systems end-to-end, taking ideas well beyond prototypes into reliable, production-grade solutions. Youll collaborate closely with enterprise and public sector clients, guiding initiatives from early proof-of-concept through to business-critical platforms used by hundreds or even thousands of people.
What Youll Do Architect agentic systems:
Take ownership of the full agent lifecycle (plan
execute
learn), including orchestration via DAGs or state machines and long-term memory design. Develop resilient tooling:
Build schemas, retry logic, rate controls, and SDKs to enable safe and extensible system use. Design memory & knowledge layers:
Deliver episodic and semantic memory services, retrieval interfaces, deduplication pipelines, and summarisation agents. Ship to production at scale:
Roll out containerised platforms across Kubernetes, serverless environments, and GPU infrastructure, with CI/CD, monitoring, and automated scaling. Harden system reliability:
Implement guardrails, latency and cost controls, checkpointing, and reviewer/critic patterns to improve output quality. Run structured evaluation:
Create automated testing frameworks using golden datasets, retrieval performance checks, and ongoing drift detection. Partner with stakeholders:
Facilitate workshops, roadmap planning, and capability assessments, turning advanced AI concepts into clear, practical plans.
What Were Looking For Required: Demonstrated experience designing, building, and running LLM-powered or agentic systems in live production environments. Solid core engineering skills across orchestration, state and memory handling, deployment pipelines, and system observability. Working knowledge of agent-based patterns and frameworks (such as LangGraph, ReAct, or chain-of-thought loops), or the capability to implement these approaches from first principles. Comfortable operating in customer-facing contexts, including leading workshops, delivering presentations, and providing technical guidance or advisory support.
Preferred: Degree or higher in AI, Computer Science, or a related technical discipline. Familiarity with PyTorch or TensorFlow, vector databases, RAG workflows, and orchestration frameworks. Experience in start-ups (versatile, hands-on generalist) or consulting environments (client-facing). Exposure to regulated sectors or compliance-heavy industries. Self-driven, entrepreneurial attitude; able to work independently and take ownership of projects.
Why Join? Real-World Impact:
Build and deploy mission-critical agentic AI systems that solve tangible problems. Cutting-Edge Challenges:
Work on orchestration and deployment problems that go far beyond standard integration. Global Collaboration:
Remote-first role offering chances to work with teams around the world. Career Growth:
Shape enterprise AI strategies and contribute meaningfully to the wider AI ecosystem. Dynamic Culture:
Join a fast-moving team at the forefront of applied AI innovation.