5-7 years of hands-on experience with Microsoft AI Foundry and Azure AI Foundry.
Proficiency in Python development for AI applications.
Experience in building and deploying AI agents and workflows.
Familiarity with LangGraph and LangSmith for orchestration and observability.
Knowledge of enterprise security, identity management, and secure AI architecture.
Experience with AI evaluation and production deployment.
Background in large enterprise or consulting environments.
Responsibilities
Define and standardize core components of the enterprise AI platform.
Establish best practices and frameworks for AI/ML application development.
Build initial applications like chatbots and AI-enabled solutions.
Demonstrate build capabilities for future development teams.
Manage access and security compliance using Copilot Studio.
Integrate with enterprise identity management systems.
Collaborate with engineering and product stakeholders as a senior individual contributor.
Benefits
Onsite work environment in Houston, TX, fostering collaboration.
Opportunity to work with cutting-edge AI technologies.
Mentorship opportunities for junior team members.
Involvement in building enterprise-scale AI applications.
Engagement with cross-functional teams and leadership on strategic initiatives.
Full Job Description
Start Date: Interview Types
Skills Microsoft AI Foundry.. Visa Types Green Card, US Citiz..
AI Engineer
Rate: $78/hr on W2 MAX
Location: Houston, TX, onsite 5 days per week
We're looking for AI Engineers for Halliburton in Houston, TX. This is a hands-on engineering role focused on building enterprise AI applications and agentic solutions, not a pure data science/research role.
Key requirements:
Strong hands-on Microsoft AI Foundry / Azure AI Foundry experience
Azure OpenAI / Azure AI Studio experience is highly relevant
Building and deploying AI agents / agentic workflows
Python development
LangGraph for agen
t/workflow orchestration
LangSmith for tracing, testing, evaluation, and observability
RAG / GenAI / LLM application development
Copilot Studio
API/tool integration and enterprise systems integration
Experience with AI evaluation, monitoring, guardrails, and production deployment
Understanding of enterprise identity, security, authorization/RBAC, and secure AI architecture
Databricks exposure is relevant
Must be hands-on technically, able to design/build solutions rather than only architect/manage
Environment: Microsoft AI Foundry, Azure OpenAI, Copilot Studio, LangGraph, LangSmith, Python, Databricks
Key Responsibilities
AI Platform Development:
Define, implement, and standardize core components of the enterprise AI platform (AI Foundry).
Establish best practices, frameworks, and reference architectures for AI/ML application development.
Application Engineering:
Build initial applications on the platform (e.g., chatbots, copilots, AI-enabled applications).
Prove out build capabilities that future dev teams will replicate and scale.
Integration & Security:
Work with Copilot Studio and Microsoft Copilot to manage access, identities, and security compliance.
Integrate with enterprise identity management and ensure secure system design.
Team & Collaboration:
Act as a senior IC while collaborating with engineering and product stakeholders.
Contribute to rebuilding a cohesive team and mentoring junior members.
Support cross-functional teams and partner with leadership on adoption strategy.
Required Skills & Experience
Strong expertise in Python development (core language for AI and data science).
Proven experience with AI/ML platform engineering or enterprise-scale data platforms.
Familiarity with Copilot Studio, Microsoft Copilot, or similar tools for enterprise AI integration.
Knowledge of identity and security integration in enterprise environments.
Background in large enterprise or consulting environments (not early-stage startup only).
Strong IC who can operate independently while collaborating with leadership.
Preferred Qualifications
Experience building enterprise AI platforms from the ground up.
Familiarity with cloud-based AI services (Azure OpenAI, AWS AI/ML, etc.).
Ability to present technical work clearly to both technical and non-technical stakeholders.
Prior experience in the oil & gas or energy sector is a plus.
