Job Opportunity: AI Systems Engineer - Atlanta, GA /Seattle, WA - 12 months + (High potential for extension)

[Venu Goud]

Job Opportunity: AI Systems Engineer

Location: Atlanta, GA /Seattle, WA

Duration: 12 months + (High potential for extension)

Send me the resumes to Ve...@techrakers.com, Only H1B'S AND USC.

                                                                                                                                                                                                                                          

Job Description:

We are seeking a versatile and highly skilled AI Systems Engineer with deep expertise in fullstack Python development, intelligent agent orchestration, and advanced context engineering. This role is central to building next-generation AI-powered applications that leverage large language models (LLMs), multi-agent workflows, and dynamic context management. You will architect and integrate scalable systems using frameworks like LangGraph and MCP, while collaborating across disciplines to deliver adaptive, intelligent solutions.

Required Skills & Qualifications:

1. Strong experience with fullstack Python development (FastAPI, Flask, Django; SQL/NoSQL databases).

2. Proven expertise in prompt engineering and context-aware LLM integration (OpenAI, Anthropic, open-source models).

3. Hands-on experience with LangGraph and MCP for agent orchestration and workflow design.

4. Familiarity with vector search, RAG pipelines, and session/context management strategies.

5. Experience integrating AI agents into production systems with cloud infrastructure (AWS, GCP, Azure).

6. Proficiency with containerization (Docker), CI/CD pipelines, and scalable distributed systems.

7. Excellent problem-solving, communication, and collaboration skills.

 

Preferred Qualifications:

1. Background in information retrieval, knowledge graphs, or search systems.

2. Experience with front-end development and data visualization tools.

3. Contributions to open-source AI, agent, or LLM frameworks.

4. Familiarity with advanced ML model serving and orchestration platforms.

 

Key Responsibilities:

Prompt & Context Engineering

2. Design and optimize prompts for LLMs to ensure accurate, contextually rich outputs across diverse use cases.

3. Architect dynamic context management systems including session memory, retrieval-augmented generation (RAG), and user personalization.

 

Agent Integration & Orchestration:

5. Develop and deploy autonomous and semi-autonomous AI agents using LangGraph and MCP.

6. Coordinate multi-agent workflows, manage state transitions, and ensure seamless model interoperability.

 

Fullstack System Development:

1. Build robust backend services and APIs using Python frameworks (FastAPI, Flask, Django).

2. Develop front-end interfaces using modern JS frameworks (React, Vue, Angular) to support end-to-end user experiences.

 

System Integration:

1. Connect agents with external data sources, vector databases, third-party APIs, and ML models.

2. Implement scalable pipelines for knowledge retrieval, model serving, and real-time interaction.