Senior AI Engineer

Advanced Tech Placement; Alpharetta (GA); On-site; USD 140,000 - 200,000; Full time

Job summary

Advanced Tech Placement is seeking a hands-on Senior AI Engineer to design and build advanced AI and agentic applications. You will work with Python, LLMs, LangChain, and LangGraph to shape scalable technical solutions.

You will lead architecture for multi-agent workflows, develop RAG pipelines, and integrate AI components with enterprise systems while prioritizing security, privacy, and performance. Expect collaboration with cross-functional teams and opportunities to influence product strategy

Qualifications

• 10 years of experience in Software Engineering, Machine Learning, Data Science, AI Engineering, or a related technical field.
• Strong hands-on Python programming experience.
• Hands-on experience building AI or agentic applications using LLMs.
• Experience with AI agent frameworks such as LangChain and LangGraph.
• Understanding of LLM behavior, tokens, context management, hallucinations, guardrails, performance and cost considerations.
• Experience with prompt engineering and agentic workflows.
• Experience with MCP (Model Context Protocol) and AI tool or skills integrations.
• Experience with LLM evaluation, testing, debugging and optimization.
• Knowledge of NLP concepts and techniques.
• Experience integrating AI apps with external tools and enterprise systems.

Responsibilities

• Design and build AI-powered and agentic applications using Python, LLMs, LangChain, and LangGraph.
• Help define technical solutions and architecture for complex AI and multi-agent workflows.
• Design and implement agent orchestration, multi-step and multi-turn workflows, tool usage, memory, and interactions between agents and external systems.
• Build and optimize RAG pipelines, including retrieval strategies, embeddings, vector search, and integration with enterprise knowledge sources.
• Contribute to the integration and use of Knowledge Graphs and structured data within AI applications.
• Work with MCP and AI skills/tool integrations to connect AI agents with external applications, APIs, and enterprise systems.
• Apply strong understanding of LLMs and Machine Learning concepts to decide on model selection, performance, cost, reliability, hallucinations, and guardrails.
• Develop and improve prompt strategies and agent behavior.
• Define and implement approaches for LLM evaluation, AI testing, debugging, and performance optimization.
• Troubleshoot complex AI workflows, including multi-turn conversations, retrieval issues, hallucinations, tool failures, and orchestration challenges.
• Help establish best practices around AI security, data privacy, and responsible AI development.
• Collaborate with engineers to translate business problems into scalable AI solutions.

Skills

Python

Machine Learning

Data Science

AI Engineering

LLMs

Tools

LangChain

LangGraph

APIs

Job description

We are seeking a hands-on Senior AI Engineer to help design and build advanced AI and agentic applications. This individual will bring strong technical depth in AI/ML, Python, LLMs, and agentic systems and will be responsible for helping shape technical solutions while remaining actively involved in development and implementation.

Responsibilities:

• Design and build AI-powered and agentic applications using Python, LLMs, LangChain, and LangGraph.
• Help define technical solutions and architecture for complex AI and multi-agent workflows.
• Design and implement agent orchestration, including multi-step and multi-turn workflows, tool usage, memory, and interactions between agents and external systems.
• Build and optimize RAG pipelines, including retrieval strategies, embeddings, vector search, and integration with enterprise knowledge sources.
• Contribute to the integration and use of Knowledge Graphs and structured data within AI applications.
• Work with MCP and AI skills/tool integrations to connect AI agents with external applications, APIs, and enterprise systems.
• Apply strong understanding of LLMs and Machine Learning concepts to make informed decisions around model selection, performance, cost, reliability, hallucinations, and guardrails.
• Develop and improve prompt strategies and agent behavior.
• Define and implement approaches for LLM evaluation, AI testing, debugging, and performance optimization.
• Troubleshoot complex AI workflows, including multi-turn conversations, retrieval issues, hallucinations, tool failures, and orchestration challenges.
• Help establish best practices around AI security, data privacy, and responsible AI development.
• Collaborate with engineers and technical teams to translate business problems into scalable AI solutions.

Requirements:

• 10 years of overall experience in Software Engineering, Machine Learning, Data Science, AI Engineering, or a related technical field.
• Strong hands-on programming experience with Python.
• Strong background in Machine Learning, Data Science, or AI/ML concepts.
• Hands-on experience building AI or agentic applications using LLMs.
• Experience with AI agent frameworks such as LangChain and/or LangGraph.
• Understanding of LLM behavior and limitations, including tokens, context management, hallucinations, guardrails, performance, and cost considerations.
• Experience with prompt engineering and agentic workflows.
• Experience with or strong familiarity with MCP (Model Context Protocol) and AI tool or skills integrations.
• Experience with LLM evaluation, testing, debugging, and optimization.
• Knowledge of NLP concepts and techniques.
• Experience working with APIs and integrating AI applications with external tools and enterprise systems.
• Strong understanding of data privacy and security considerations when developing AI applications.
• Ability to independently analyze technical problems and recommend appropriate AI solutions and designs.

Preferred Skills:

• Experience with multi-agent systems and orchestration.
• Experience with Knowledge Graphs.
• Experience with vector databases, embeddings, and semantic search.
• Experience deploying AI/ML applications in cloud environments.
• Experience building production-grade AI applications in an enterprise environment.