Lead AI Engineer
Not Disclosed•Full-TimeOn-site
location_onComanche County, Texas, United States
About the Role
We are seeking a Senior AI Engineer to design, build, and operate production-grade Agentic AI systems that power intelligent assistants and autonomous workflows across regulated enterprise environments. This role is critical for bridging the gap between experimental AI capabilities and safe, reliable, enterprise-scale operations.
You will focus on LLM-based agents, multi-agent orchestration, and rigorous guardrails, ensuring that AI responses are accurate, auditable, and compliant with strict regulatory standards. The position offers direct exposure to Copilot Studio, LangChain, LangGraph, and enterprise CI/CD practices, allowing you to shape how agents interact with real business workflows.
What Success Looks Like
In this role, you will ensure that agents consistently generate accurate, policy-compliant, and explainable responses. Your work will enable new agent capabilities to move from prototype to production safely and quickly, with CI/CD pipelines that catch regressions before they reach users. Ultimately, you will build AI systems that are trusted by both business users and risk/compliance teams, preventing hallucinations and incorrect guidance at scale.
Application Process
For applications and inquiries, please contact hirings@openkyber.com.
Work location
Work model: On-site
Comanche County, Texas, United States
Texas
Key Responsibilities
- check_circleDesign and implement Agentic AI systems using LangChain and LangGraph
- check_circleBuild multi-agent workflows for intent classification and decision orchestration
- check_circleDevelop tool-using agents for retrieval, rules engines, and enterprise services
- check_circleOptimize prompt strategies and state management to minimize hallucinations
- check_circleBuild and extend agents using Copilot Studio and Power Platform frameworks
- check_circleIntegrate custom Python-based agents with Copilot runtime and enterprise data sources
- check_circleImplement AI guardrails for policy enforcement and output validation
- check_circleEnsure agents comply with enterprise risk, regulatory, and data security standards
- check_circleBuild automated agent testing frameworks to validate intent and response accuracy
- check_circleImplement offline and online evaluation using golden datasets and confidence scoring
- check_circleDevelop CI/CD pipelines for AI agents including prompt versioning and model updates
- check_circleIntegrate logging, observability, alerts, and performance metrics for agent behavior
Requirements
- verifiedStrong Python engineering experience
- verifiedHands-on experience with LangChain and/or LangGraph
- verifiedExperience building Agentic AI systems
- verifiedUnderstanding of LLM tooling, RAG, function/tool calling, and orchestration patterns
- verifiedExperience implementing CI/CD pipelines for ML or AI-driven systems
- verifiedProven experience in testing LLM outputs and agent behavior
- verifiedExperience with enterprise AI platforms (Copilot Studio, Power Platform, or equivalent)
- verifiedFamiliarity with microservices, APIs, event-driven systems, and cloud-native design
- verifiedExperience designing governed, production-ready AI architectures
Nice to Have
Experience with Copilot Studio custom agents or connectors. Knowledge of LLMOps / AI Ops practices. Experience in regulated domains (financial services, healthcare, compliance-heavy environments). Familiarity with evaluation frameworks, agent observability tools, and policy engines. Exposure to graph-based reasoning or knowledge graphs.
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Frequently asked questions about Lead AI Engineer at Openkyber
What does a Lead AI Engineer at Openkyber do?expand_more
A Lead AI Engineer at Openkyber is responsible for the following: Design and implement Agentic AI systems using LangChain and LangGraph; Build multi-agent workflows for intent classification and decision orchestration; Develop tool-using agents for retrieval, rules engines, and enterprise services; and Optimize prompt strategies and state management to minimize hallucinations.
What are the requirements for this Lead AI Engineer role?expand_more
Openkyber is looking for candidates who meet the following requirements: Strong Python engineering experience; Hands-on experience with LangChain and/or LangGraph; Experience building Agentic AI systems; Understanding of LLM tooling, RAG, function/tool calling, and orchestration patterns; Experience implementing CI/CD pipelines for ML or AI-driven systems; and Proven experience in testing LLM outputs and agent behavior.
Where is the Lead AI Engineer role at Openkyber located?expand_more
Lead AI Engineer at Openkyber is based in Comanche County, Texas, United States. This is a on-site role.
Is this Lead AI Engineer job remote, hybrid, or on-site?expand_more
Openkyber has listed this Lead AI Engineer role as on-site.
How much experience is required for this Lead AI Engineer role?expand_more
Candidates for Lead AI Engineer at Openkyber should have lead.
What skills do you need for the Lead AI Engineer role at Openkyber?expand_more
Key skills for Lead AI Engineer at Openkyber include Python; Langchain; Langgraph; Copilot Studio; Power Platform; Ci/cd; LLM; and Rag.
What category does the Lead AI Engineer role belong to?expand_more
Lead AI Engineer at Openkyber is part of the it job category on Recrutus.