Agentic AI Engineer

Socket.dev; Dallas (TX); Hybrid; USD 150,000 - 210,000; Full time

Benefits offered by this job

ONSITE

Competitive salary

Opportunity for advancement

Job summary

Socket.dev is seeking an experienced AI Engineer to design and build enterprise-grade AI applications using Agentic AI, LLMs, and orchestration frameworks. The role focuses on multi-agent systems, conversational AI, and production-grade LLM integrations.

The ideal candidate has hands-on experience with LangGraph, LangChain, and modern cloud tech, plus strong Python and ML model integration skills. Hybrid Dallas, 12+ month engagements.

Qualifications

• Bachelor’s or Master’s degree in CS/AI/ML or related field.
• 5+ years of software engineering experience.
• 2+ years building Generative AI or LLM-based apps.
• Strong experience with LangGraph or LangChain.
• Experience designing multi-agent AI systems.
• Experience with MCP or similar tool integration architectures.
• Strong understanding of LLM concepts and prompt engineering.
• Hands-on Python experience and ML framework knowledge.
• Experience building REST APIs and cloud deployments.
• Experience with AWS/Azure/GCP.

Responsibilities

• Design, develop, and deploy agent-based AI apps using LangGraph/ LangChain.
• Build scalable multi-agent workflows with planning, execution, state management.
• Develop reusable orchestration tools and components for enterprise AI.
• Integrate Model Context Protocol clients and tool ecosystems.
• Develop conversational AI with memory, reasoning, and tool invocation.
• Integrate ML models for inference and feedback loops.
• Apply RAG, vector search, and knowledge retrieval where applicable.
• Implement LLMOps: prompt versioning, monitoring, and testing strategies.
• Collaborate with engineering, product, and business teams on enterprise AI.
• Stay current with agentic and generative AI tech and best practices.

Skills

Python

LangGraph

LangChain

Multi-agent systems

LLM orchestration

Prompt engineering

REST APIs

Cloud platforms

ML integration

Education

Bachelor’s or Master’s in CS/AI/ML/Data Science

Tools

TensorFlow

PyTorch

Scikit-learn

Docker

Kubernetes

LangGraph

LangChain

Job description

Benefits

• ONSITE


• Competitive salary


• Opportunity for advancement

AI Engineer – Agentic AI | LLM | LangGraph | LangChain

Location: Dallas, TX (Hybrid)

Duration: 12+ Months

Interview Process: Technical Screening + Final In-Person Interview (Mandatory)

Compensation : Depends on Experience, Skills.

We are seeking an experienced AI Engineer with strong expertise in Agentic AI, Large Language Models (LLMs), and AI orchestration frameworks to design and develop enterprise-grade AI applications.

The ideal candidate will have hands-on experience building multi-agent systems, conversational AI solutions, and production-ready LLM applications using modern AI frameworks and cloud technologies.

This role requires a strong software engineering background with practical experience in AI orchestration, machine learning integration, prompt engineering, and LLMOps.

Responsibilities

• Design, develop, and deploy agent-based AI applications using LangGraph, LangChain, and similar orchestration frameworks.


• Build scalable multi-agent workflows with intelligent task planning, execution, and state management.


• Develop reusable tools, workflows, and orchestration components for enterprise AI applications.


• Design and integrate Model Context Protocol (MCP) clients and tool ecosystems.


• Build conversational AI applications with contextual memory, reasoning, and dynamic tool invocation.


• Develop and integrate REST APIs and external enterprise systems into AI workflows.


• Integrate machine learning models using TensorFlow, PyTorch, or Scikit-learn for inference, prediction, and feedback loops.


• Implement Retrieval-Augmented Generation (RAG), vector search, and knowledge retrieval solutions where applicable.


• Apply LLMOps best practices including prompt engineering, prompt versioning, evaluation, monitoring, logging, observability, and performance optimization.


• Define and execute testing strategies for AI applications, including unit testing, workflow validation, scenario simulation, regression testing, and agent behavior evaluation.


• Optimize AI systems for scalability, reliability, security, and cost efficiency.


• Collaborate with engineering, product, and business teams to deliver enterprise AI solutions.


• Stay current with emerging technologies, frameworks, and best practices in Agentic AI and Generative AI.

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field.


• 5+ years of software engineering experience.


• 2+ years of hands-on experience developing Generative AI or LLM-based applications.


• Strong experience with LangGraph, LangChain, or similar AI orchestration frameworks.


• Experience designing and implementing multi-agent AI systems.


• Experience with Model Context Protocol (MCP) or similar tool integration architectures.


• Strong understanding of LLM architecture, prompt engineering, function calling, tool usage, memory management, and agent orchestration.


• Hands-on experience with Python.


• Experience with TensorFlow, PyTorch, or Scikit-learn.


• Experience building REST APIs and microservices.


• Experience working with cloud platforms such as AWS, Azure, or GCP.


• Experience deploying AI applications into production environments.


• Strong problem-solving and communication skills.

Preferred Qualifications

• Experience with CrewAI, AutoGen, Semantic Kernel, or similar frameworks.


• Experience with vector databases such as Pinecone, Weaviate, Chroma, Milvus, or FAISS.


• Experience implementing RAG architectures.


• Familiarity with LangSmith, Weights & Biases, Arize AI, or other LLM observability platforms.


• Experience with Docker, Kubernetes, CI/CD, and cloud-native deployments.


• Knowledge of distributed systems and scalable AI architecture.