Quick Overview
Salary
$120k - $140k/yr
Work Type
On Site
Level
Mid Senior
Job Description
Benefits:
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 Google Cloud Platform.
* 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.
Compensation: $120,000.00 - $140,000.00 per year
About Us
We work to deliver profitability in your business - with effective communication, consulting, and interactive solutions. Following an Agile Work Approach, we make sure you get the ideal solutions at minimum expenses.
Work Approach
Our Philosophy
Our Philosophy starts-and-ends at the Client-first approach. Be it understanding your business requirements to choosing the right technologies, we work as a collective team that takes all the possible steps to grow continuously towards our common goal.
Work Policy
We promote a collaborative work environment. We involve everyone working in the organization in community decisions and encourage them to think from a broader perspective. Our work process promotes flexibility and we maintain a high level of discipline at different levels of execution.
The Future
SelectMinds have years of experience in the domain helps us understand the need-of-the-hour better. This understanding drives us to a better future with every minute ticking. We believe we will be taking off major businesses from their flagship positions, with the products we are eyeing today.
- 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 Google Cloud Platform.
* 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.
Compensation: $120,000.00 - $140,000.00 per year
About Us
We work to deliver profitability in your business - with effective communication, consulting, and interactive solutions. Following an Agile Work Approach, we make sure you get the ideal solutions at minimum expenses.
Work Approach
Our Philosophy
Our Philosophy starts-and-ends at the Client-first approach. Be it understanding your business requirements to choosing the right technologies, we work as a collective team that takes all the possible steps to grow continuously towards our common goal.
Work Policy
We promote a collaborative work environment. We involve everyone working in the organization in community decisions and encourage them to think from a broader perspective. Our work process promotes flexibility and we maintain a high level of discipline at different levels of execution.
The Future
SelectMinds have years of experience in the domain helps us understand the need-of-the-hour better. This understanding drives us to a better future with every minute ticking. We believe we will be taking off major businesses from their flagship positions, with the products we are eyeing today.
Skills
Docker
Microservices
AWS
Machine Learning
Scikit-learn
Agile
Azure
Generative AI
Google Cloud
Kubernetes
LLM
PyTorch
Python
REST
TensorFlow
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