Agentic AI Architect​/Engineer

Title:

Agentic AI Architect/Engineer

Location:

Dallas TX
Duration: 12 months with extension
Work Requirements: US Citizen, GC Holders or Authorized to Work in the U.S.
Skillset /

Experience:

Job Description
As a Senior Engineer 2 – Architect on the Agentic System Layer (ASL) team, you will define and drive the technical architecture of client’s agentic AI platform. You will lead the design and evolution of multi-agent orchestration systems, tool-use frameworks, and LLM integration pipelines, ensuring the platform is reliable, secure, scalable, and production-ready.
Day-to-day responsibilities include:

• Designing and evolving the architecture for multi-agent orchestration systems, tool-use frameworks, and LLM integration pipelines.
• Establishing architectural patterns for agent reliability, observability, security, and guardrails at production scale.
• Leading technical design reviews and documenting key architectural decisions through Architecture Decision Records (ADRs).
• Collaborating with ML engineers and software engineers to ensure platform components are scalable, secure, maintainable, and aligned with enterprise architecture standards.
• Evaluating and integrating emerging agentic AI frameworks, including Lang Graph, CrewAI, Semantic Kernel, and Auto Gen.
• Defining API contracts, data flow patterns, and integration standards across the AI platform ecosystem.
• Mentoring engineers on best practices for designing, developing, deploying, and operating production-grade AI systems.
• Evaluating architectural trade-offs and establishing design patterns that support high availability, fault tolerance, graceful degradation, and operational excellence.

Top 3 Mandatory Skills and Experience
1. Software Architecture and AI/ML Platform Design

• 10+ years of software engineering and architecture experience, including at least 3 years designing AI/ML platform systems.
• Hands-on experience with LLM orchestration frameworks such as Lang Chain, Lang Graph, Semantic Kernel, or similar technologies.
• Proven ability to define enterprise-level architecture for complex, distributed software platforms.

2. Distributed Systems and Modern Software Architecture

• Deep expertise in distributed systems, microservices architecture, event-driven design patterns, and API development using REST and/or gRPC.
• Strong proficiency in Python and at least one additional programming language:
  Java, Go, or Type Script.
• Experience defining scalable integration patterns, service boundaries, API contracts, and data flow standards across enterprise platforms.

3. Production-Grade Agentic AI and LLM Applications

• Demonstrated experience building, deploying, and supporting production agentic AI systems or LLM-powered applications at scale—not just proofs of concept or prototypes.
• Strong understanding of prompt engineering, agent tool use, multi-agent orchestration, retrieval-augmented generation (RAG), and LLM integration patterns.
• Experience implementing agent reliability, observability, evaluation, error handling, and production monitoring strategies.

Nice-to-Have Skills

• Experience with Kubernetes, container orchestration, and cloud platforms such as AWS, Azure, or GCP.
• Familiarity with MLOps/LLMOps tooling and practices.
• Experience with vector databases such as Pinecone, Weaviate, or pgvector.
• Knowledge of knowledge graphs and their integration with AI applications.
• Experience designing multi-agent system patterns and implementing agent evaluation, testing, and benchmarking frameworks.
• Airline, aviation, travel, or other large-scale, mission-critical enterprise domain experience.
• TOGAF or a comparable enterprise architecture certification.

Ideal Candidate Profile

The ideal candidate is a seasoned software architect with 10+ years of experience who has successfully designed,…