Job Description
We are looking for an AI Engineer to design, develop, and scale LLM-powered applications from prototype through production. This role is ideal for a software engineer with strong Python backend experience and recent hands-on work building GenAI systems (RAG, chatbots, and orchestration frameworks like LangChain/LangGraph).
This is a cross-pod role: you will partner with multiple teams to enable and accelerate AI capabilities across the organization, rather than being dedicated to a single pod.
What You’ll Do
• Design, develop, and maintain LLM-based applications from proof-of-concept to production-grade systems
• Build robust backend services and APIs in Python using FastAPI and/or Flask to power AI features
• Integrate and orchestrate large language models using frameworks such as LangChain and LangGraph
• Develop and iterate on agentic AI workflows (tool use, planning, multi-step reasoning) to support complex tasks
• Apply modern agent patterns such as ReAct and Reflection to improve reliability and output quality
• Implement and maintain RAG (Retrieval-Augmented Generation) architectures, including:
○ Vector databases, retrievers, embeddings, and indexing strategies
○ Knowledge base/document management and refresh workflows
○ Prompting and evaluation approaches for grounding and quality
• Build chat-based LLM applications and conversational UX patterns for web experiences
• Scale GenAI applications in production with a focus on:
○ Performance and latency optimization
○ Cost management and usage efficiency
○ Observability, monitoring, and incident troubleshooting
• Collaborate across teams to define best practices, reusable components, and standards for AI delivery
We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to HR@insightglobal.com.To learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/.
Required Skills & Experience
• Strong software engineering foundation with production backend experience in Python
• Experience building and shipping LLM-enabled products (prototype → production)
• Hands-on experience with FastAPI/Flask and API design (auth, rate limits, retries, error handling, versioning)
• Practical experience integrating LLMs via frameworks such as LangChain and/or LangGraph
• Recent experience (last 2–5 years) building one or more of:
○ RAG systems (vector DB + retrievers + knowledge base management)
○ Chatbots or conversational experiences embedded into a website or application
• Familiarity with production concerns for GenAI systems (evaluation, monitoring, and deployment readiness)
Nice to Have Skills & Experience
• Experience building agentic AI systems with tool use, planning, and multi-step execution
• Experience with ReAct and Reflection patterns (or similar agent reliability techniques)
• Experience with vector databases (e.g., Pinecone, Weaviate, Milvus, pgvector) and retrieval tuning
Experience with LLM observability tools and practices (tracing, token usage, latency profiling, prompt/version management)
Benefit packages for this role will start on the 1st day of employment and include medical, dental, and vision insurance, as well as HSA, FSA, and DCFSA account options, and 401k retirement account access with employer matching. Employees in this role are also entitled to paid sick leave and/or other paid time off as provided by applicable law.