LLM Engineer

Job Description

• Design and build RAG pipelines, retrieval systems, and search capabilities

• Develop and maintain LLM-powered backend services and APIs

• Implement document ingestion, indexing, and embedding pipelines

• Work cross-functionally with product and engineering teams to deliver features

• Use a data-driven approach to debug, optimize, and improve systems

• Own features end-to-end, ensuring performance, scalability, and reliability

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 View email address on click.appcast.io learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy:

Skills and Requirements

Insight Global is hiring an LLM Engineer to join a high-impact development team focused on building and scaling LLM-powered features in production applications. This individual will work hands-on across backend services, APIs, and AI systems, owning features end-to-end while leveraging modern AI engineering practices.

• Hands-on experience building RAG (Retrieval-Augmented Generation) systems end-to-end

• Strong experience with LLM APIs (OpenAI, Anthropic) and GenAI integrations

• Proficiency in Python (primary) with Java exposure or ability to work in Java environments

• Experience with vector databases, embeddings, and semantic search

• Strong experience with cloud platforms (AWS, Azure, or GCP) and REST APIs

• Practical use of AI-assisted coding tools (Copilot, Cursor, Claude, agentic tools)

• Experience delivering LLM-powered features in production environments (not just POCs)

• Strong backend engineering fundamentals (scalability, performance, system design)

Compensation & Benefits:

Exact compensation may vary based on several factors, including skills, experience, and education ($70-75/HR). This position may also be eligible for bonuses, benefits, or other forms of compensation, depending on the client and employment type. - Experience with Elasticsearch / OpenSearch / Solr

• Familiarity with LangChain, LlamaIndex, or similar frameworks

• Experience with LLM guardrails, monitoring, and observability

• Exposure to multi-agent systems / agentic workflows

• Experience with event-driven architectures and messaging systems

• Background in NLP / ML concepts applied to LLM systems