AI Engineer
Role details
Job location
Tech stack
Job description
We are seeking an experienced AI Solutions Engineer to embed directly within Product Service Lines (PSLs) and deliver production-ready, multi-agent AI systems. This role blends hands-on engineering, solution architecture, stakeholder partnership, and operational ownership. You will take AI solutions from discovery through go-live, ensuring reliability, adoption, and measurable impact.
You will operate as the primary AI engineering point of contact for short, sprint-based engagements, owning delivery end-to-end while helping standardize patterns that scale across the organization. This role is remote if you are located in Dallas.
Key Responsibilities1. Embedded Delivery & Stakeholder Partnership
- Embed within assigned PSLs as the primary AI engineering lead.
- Lead discovery sessions with PSL subject matter experts to clarify:
- Business goals and success criteria
- Workflow realities and user adoption requirements
- Technical, data, and compliance constraints
- Deliver bi-weekly demos (minimum) and maintain continuous stakeholder alignment from discovery through go-live.
- Execute against PSL sponsor priorities while maintaining engineering rigor, security, and production readiness.
- Solution Architecture & Multi-Agent Development
- Translate business requirements into:
- Agent architectures
- Data and integration requirements
- Clear execution plans
- Design and build multi-agent systems using:
- Azure AI Foundry
- LangGraph (routing, state, memory, tools, retries, fallbacks, guardrails)
- Integrate agents with enterprise systems as needed (e.g., SharePoint, Teams, Azure AI Search, Databricks, SQL, internal/external APIs).
- Make pragmatic engineering tradeoffs to deliver value quickly without sacrificing maintainability, reliability, or security.
- Production Deployment & Operational Readiness (You Own This)
- Deploy solutions into production, primarily as Azure-hosted services, typically using containers.
- Implement production-grade practices including:
- Environment separation
- Configuration and secrets management
- Telemetry-by-default
- Rollback-friendly release strategies
- Design solutions that operate effectively within enterprise constraints (identity, access, compliance, platform standards) without requiring deep specialization in any single corporate system.
- Agent Ops by Design (Tracing, Logging, Registration)
- Ensure all delivered agents follow established observability and tracing standards.
- Instrument systems using supported tooling such as:
- Application Insights
- Agent 365
- LangSmith
- Contribute to defining and adopting agent registration standards, including:
- Required metadata
- Automated population
- Consistent inventory and visibility across the organization
- Help standardize foundational delivery patterns so teams can scale without rebuilding core infrastructure.
- Evaluation Discipline & Performance Improvement
- Establish robust evaluation approaches that combine:
- Curated golden datasets
- Human review workflows
- Automated testing (pre- and post-go-live)
- Create and maintain evaluation datasets as first-class delivery artifacts:
- Labeling strategies
- Edge-case coverage
- Regression test packs
- Clearly explain evaluation metrics:
- How they're calculated
- When they're reliable
- How they drive concrete system improvements (not "metrics theater").
- Reusable Patterns & Enablement (Avoiding Dev Bottlenecks)
- Create reusable assets such as:
- Reference architectures
- Templates and scaffolds
- Test harnesses
- Practical "how-to" playbooks
- Coach and enable other teams building agents (Copilot Studio experience a plus) by sharing:
- Delivery patterns
- Guardrails
- Integration guidance
- Operational expectations
Requirements
- Strong experience designing and delivering production AI systems.
- Hands-on experience with agent-based architectures and modern LLM orchestration.
- Azure-native development and deployment experience.
- Solid software engineering fundamentals (testing, observability, CI/CD mindset).
- Ability to communicate clearly with both technical and non-technical stakeholders.
- Comfortable working in ambiguous, fast-moving environments with real delivery ownership.
Nice to Have
- Experience with Copilot Studio enablement.
- Prior work in enterprise-scale AI platforms.
- Experience creating internal standards, templates, or developer enablement materials.
Benefits & conditions
This is a Contract to Hire position based out of Dallas, TX.
Pay and Benefits
The pay range for this position is $70.00 - $90.00/hr.
Eligibility requirements apply to some benefits and may depend on your job classification and length of employment. Benefits are subject to change and may be subject to specific elections, plan, or program terms. If eligible, the benefits available for this temporary role may include the following: * Medical, dental & vision * Critical Illness, Accident, and Hospital * 401(k) Retirement Plan - Pre-tax and Roth post-tax contributions available * Life Insurance (Voluntary Life & AD&D for the employee and dependents) * Short and long-term disability * Health Spending Account (HSA) * Transportation benefits * Employee Assistance Program * Time Off/Leave (PTO, Vacation or Sick Leave)
Workplace Type
