Quick Overview
Job Description
Job Title- AI Engineer / AI Builder
Location- Springfield, IL (Onsite)
Important Note: looking for public sector candidate only
Note : Travel cost will be paid by client
Job Description:
We are looking for a hands-on AI Engineer / AI Builder to prototype, develop, and deploy internal AI-powered tools and workflow automations. The ideal candidate is a strong coder who can quickly turn business requirements into working AI solutions and proof-of-concepts.
Key Responsibilities:
· Build and prototype AI-powered internal tools, applications, and automations.
· Develop solutions using Python and modern AI/ML frameworks and APIs.
· Integrate LLMs, Generative AI APIs, and AI agents into internal workflows.
· Build RAG-based applications, document processing, chatbots, and intelligent assistants.
· Develop integrations with internal systems, databases, APIs, and SaaS platforms.
· Create rapid POCs/MVPs, test ideas, and iterate based on user feedback.
· Automate repetitive business processes using AI and workflow automation.
· Work with stakeholders to identify high-value opportunities for AI adoption.
· Deploy and maintain AI prototypes in cloud or internal environments.
· Ensure solutions are secure, scalable, reliable, and practical for business use.
Required Skills:
· Strong hands-on Python development experience.
· Experience building Generative AI / LLM applications.
· Experience with OpenAI, Azure OpenAI, Anthropic, Gemini, or similar LLM APIs.
· Strong understanding of prompt engineering, embeddings, vector databases, and RAG.
· Experience with REST APIs, JSON, databases, and system integrations.
· Experience building AI agents or agentic workflows.
· Familiarity with LangChain, LlamaIndex, Semantic Kernel, or similar frameworks.
· Experience with Git, Docker, and cloud platforms (AWS/Azure/Google Cloud Platform).
· Strong problem-solving skills and ability to work independently in a fast-paced environment.
Nice to Have:
· Experience with Power Automate, n8n, Zapier, or similar automation platforms.
· Experience with FastAPI, Streamlit, or similar tools for quickly building internal applications.
· Experience with Azure AI / AWS Bedrock / Google Vertex AI.
· Knowledge of AI security, governance, and responsible AI practices.
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