Agentic AI Lead - Martech

InfoVision Inc.; Irving (TX); On-site; USD 140,000 - 230,000; Full time

Job summary

InfoVision Inc. in Irving, Texas, seeks an experienced AI/ML engineer with 12+ years IT experience and 4+ years in AI/ML, to design and deploy agentic and multi-agent systems, including agent orchestration, inter-agent communication, and production-grade engineering practices.

You will translate business needs into AI/ML workflows, assess outputs across agents and tools, and build scalable MCP server patterns on GCP/BigQuery.

Qualifications

• Hands-on experience on AI/ML projects in last 3–4 years
• Experience with agentic AI or GenAI applications
• Experience designing, building and deploying agentic workflows

Responsibilities

• Architect, build, and scale agentic/multi-agent solutions
• Oversee agent orchestration and inter-agent communication
• Address failure handling and production readiness
• Translate business needs into AI/ML workflows
• Evaluate and optimize agent outputs across tools and data sources
• Design MCP server patterns for secure, scalable integration

Skills

Python

Prompt Engineering

LangChain

LangGraph

Google ADK

MetaRouter

Segment

Tealium

GrowthLoop

Optimizely

Agentic AI

Inter-agent communication

MCP servers

Agent orchestration

GCP/BigQuery

Education

B.S. or M.S. in CS/AI

Tools

SOTA LLMs

Google ADK

LangChain

Job description

• Overall 12+ years of IT industry experience.
• Education: B.S. or M.S. in Computer Science, AI, or a related field is preferred.
• Experience: pref. in Data and AI, 4+ years in AI/ML engineering are preferred, with 2+ years specifically focused on agentic AI or GenAI applications.

Mentioning below skills are required in hands-on experience on projects in the last 3-4 yrs.

• Python
• Prompt Engineering
• Hands-on experience with SOTA LLMs, Langraph/LangChain, Google ADK
• Tag routing experience with MetaRouter / Segment / Tealium and Martech tools like Growthloop or Optimizely
• Hands-on experience architecting, building and scaling complex Agentic and multi-agent solutions, including agent orchestration, inter-agent communication, conflict resolution, failure handling and production-grade Agentic AI engineering practices.
• Proven experience identifying, evaluating and resolving conflicting information, reasoning or recommendations across agents, tools and data sources.
• Hands-on proficiency designing, building and consuming MCP servers, including efficient tool/resource design, secure integration and scalable, sustainable implementation patterns.
• Relevant demonstrable experience building agentic workflows with agents that reason, capture feedback, and self-learn to improve subsequent flows.
• Agentic RAG/RAG/GraphRAG framework
• Evaluate and optimize Agent output and performance, including reliability, observability, context management, failure/degradation handling and production readiness.
• Ability to interact with business teams and convert business needs to AI/ML workflows - Must demonstrate end-to-end business context — not just technical implementation.
• SQL/BigQuery/GCP, with hands-on experience designing and deploying AI/Agentic solutions on GCP strongly preferred.

Preferred skills:

• Redis, Context Engineering; demonstrable experience with A2A (Agent2Agent) protocol and interoperable agent-to-agent communication patterns is a strong plus.
• Preferred background in Telecom, with subject matter knowhow of customer touchpoint processes and CX workflows.