Job ID: JOB_ID_416
Role Overview
We are seeking a highly skilled and experienced GenAI / Agentic AI Engineer to join our innovative team. This role is pivotal in designing and deploying next-generation AI systems that leverage Large Language Models (LLMs) to solve complex business problems. With a focus on Agentic AI, you will be responsible for creating autonomous and semi-autonomous agents capable of sophisticated task planning and execution. This position requires a deep understanding of the intersection between machine learning, software engineering, and business logic.
Key Responsibilities
- Design, build, and deploy Agentic AI systems using state-of-the-art LLMs such as OpenAI, Azure OpenAI, and Anthropic.
- Create autonomous and semi-autonomous AI agents for task planning, decision-making, and execution within enterprise environments.
- Implement multi-agent workflows, tool-using agents, and orchestration frameworks like LangGraph or CrewAI.
- Integrate GenAI solutions with enterprise systems, APIs, and diverse data sources to drive business value.
- Optimize prompt engineering, memory management, reasoning capabilities, and feedback loops for agents.
- Ensure the scalability, reliability, and security of AI-driven solutions in production environments.
Technical Requirements
- 9-15 years of professional experience with a strong background in AI/ML and software development.
- Strong hands-on experience with Generative AI & LLMs (OpenAI, Azure OpenAI, Anthropic, etc.).
- Experience in Agentic AI frameworks such as LangChain, LangGraph, AutoGen, CrewAI, or similar.
- Proficiency in Python is mandatory; knowledge of FastAPI/Flask is highly desirable.
- Experience with vector databases such as Pinecone, FAISS, Weaviate, or Chroma.
- Deep understanding of RAG (Retrieval-Augmented Generation) architectures and implementation.
- Exposure to cloud platforms including AWS, Azure, or GCP.
The Evolution of Agentic AI
In the current landscape of 2026, the shift from simple LLM wrappers to complex Agentic AI systems is paramount. This role focuses on the orchestration of multiple agents that can interact with external tools and databases. You will be at the forefront of implementing Model Context Protocol (MCP) architectures, allowing for seamless tool integration and data retrieval. The complexity of managing agent sessions and long-term memory is a core challenge you will tackle daily. You will be expected to understand the definitions and capabilities of Agents and their components such as MCPs and tools, and how to consume tools on an MCP server effectively.
Enterprise-Grade AI Implementation
Building for production requires more than just a working prompt. You will implement robust evaluation frameworks to measure LLM response quality, ensuring that guardrails are in place to prevent hallucinations and maintain brand safety. Your experience with vector databases will be crucial for optimizing RAG pipelines, ensuring that agents have access to the most relevant and up-to-date information. Furthermore, you will collaborate with DevOps teams to establish efficient LLMOps pipelines, facilitating continuous integration and deployment of AI models. Prior experience in building AI copilots, chatbots, or workflow automation agents will be a significant advantage in this role.
Special Requirements
highly preferred onsite/hybrid in Cummings, GA; hands-on coding is must; experience with MCPs and agents as tools
Compensation & Location
Salary: $190,000 – $275,000 per year (Estimated)
Location: Cummings, GA
Recruiter / Company – Contact Information
Recruiter / Employer: Analyticssol
Email: shiva@analyticssol.com
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