Lead Agentic AI Developer

InfoVision Inc.; Irving (TX); On-site; USD 150,000 - 210,000; Full time

Job summary

InfoVision Inc. in Irving, TX seeks a Lead Agentic AI Developer to architect and operationalize enterprise-grade agentic systems across Google ADK, LangGraph, CrewAI, and AutoGen.

The role requires guiding framework selection, designing robust multi-agent workflows, and delivering a production-ready system integrated with enterprise data and APIs. In this 12-month onsite engagement, you will establish human-in-the-loop controls, memory management, RAG pipelines, and scalable cloud deployments on

Qualifications

• 7+ years in software or AI/ML, with at least 3 years deploying production multi-agent or LLM-based systems at enterprise scale.
• Experience architecting enterprise-scale agentic or LLM-based systems.
• Deep Python proficiency for production agentic development.
• Experience with Google Cloud Platform integrations (Vertex AI, Cloud Run, BigQuery, Cloud Storage).
• Knowledge of MCP and A2A protocols; RAG and vector search concepts.
• Bachelor's degree in CS/Engineering or equivalent experience.

Responsibilities

• Architect and deliver production-grade multi-agent systems using Google ADK 2.0+ and other frameworks.
• Design complex agentic workflows with branching, loops, and parallel patterns.
• Define inter-agent communication standards with MCP and A2A protocols.
• Set human-in-the-loop controls and safety guardrails for compliant behavior.
• Build RAG pipelines with memory management and accuracy improvements.
• Deploy on Google Cloud with high availability and low latency SLAs.
• Mentor teams and drive enterprise agentic roadmap with stakeholders.

Skills

Multi-agent systems design

Python production development

Prompt engineering & context

Framework evaluation

Memory management

RAG system design

Architectural leadership

Education

Bachelor's degree in Computer Science or Engineering

Equivalent practical experience

Tools

Google ADK

LangGraph

CrewAI

AutoGen

Vertex AI

BigQuery

Cloud Run

Pinecone

Elasticsearch

Job description

Please review the below job requirement and let me know if you are good to submit with the below details filled and your latest resume ASAP.

Lead Agentic AI Developer – Google ADK Workflows

Location: Irving TX – 3 days onsite

Duration: 12 months

Role Summary

This role leads the design, architecture, and operationalization of enterprise-grade agentic AI systems spanning multiple orchestration frameworks — including Google's Agent Development Kit (ADK), LangGraph, CrewAI, and AutoGen — deployed at scale on Google Cloud. Embedded within Clients AI engineering practice, the Lead Agentic AI Developer serves as the technical authority for agentic workflow design, framework selection, and cross-agent communication standards using MCP and A2A protocols. In the first 90 days, you will own the delivery of a production multi-agent system fully instrumented with evaluation, observability, and human-in-the-loop controls, integrated with enterprise data and API ecosystems.

Key Responsibilities

• Architect and lead delivery of production-grade multi-agent systems using Google ADK 2.0+, LangGraph, CrewAI, and AutoGen — selecting the right framework per workload based on compliance, auditability, and performance requirements.
• Design complex agentic workflows including branching logic, conditional execution, loop-based self-correction, and parallel fan-out patterns across Google Cloud and enterprise environments.
• Establish and enforce inter-agent communication standards using MCP (Model Context Protocol) and A2A (Agent-to-Agent) protocols to enable seamless integration of heterogeneous agent ecosystems.
• Define human-in-the-loop controls, autonomy boundaries, and agent guardrail frameworks that ensure safe, compliant, and auditable behavior in regulated enterprise contexts.
• Build and maintain RAG and GraphRAG pipelines grounded in enterprise knowledge — including chunking strategies, hybrid vector search, and long-term agent memory management — to maximize factual accuracy and minimize hallucination.
• Deploy and operate agentic infrastructure on Google Cloud (Vertex AI, Cloud Run, Agent Engine) with high availability, security, and low-latency SLAs at scale.
• Create and industrialize automated evaluation frameworks that measure agent reasoning correctness, tool-use accuracy, latency, and business-outcome metrics across all deployed workflows.
• Mentor engineering teams, drive adoption of agentic best practices, and collaborate with product, AI research, and architecture stakeholders to define the enterprise agentic AI roadmap.

Required Qualifications

• 7+ years of experience in software engineering or AI/ML, with at least 3 years directly architecting and deploying production multi-agent or LLM-based systems at enterprise scale.
• Hands-on expertise across multiple agentic frameworks — including Google ADK, LangGraph, CrewAI, and/or AutoGen — with the ability to evaluate and select frameworks based on technical and business requirements.
• Deep proficiency in Python for production agentic development; strong command of prompt engineering, context management, and agentic design patterns (ReAct, Plan-and-Execute, state graphs).
• Demonstrated experience with Google Cloud Platform (Vertex AI, Cloud Run, BigQuery, Cloud Storage) and integration of agentic systems using MCP and A2A protocols.
• Strong background in RAG system design, vector store integration (Vertex AI Vector Search, Pinecone, Elasticsearch), and context engineering strategies including memory management and prompt compression.
• Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.