AI Engineer

You will work across the AI layer of the platform, contributing to retrieval pipelines, agent workflows, and model evaluation. This role is highly hands-on and empirical - you’ll run experiments, measure outcomes, and iterate quickly.

You’ll partner closely with the Senior AI Engineer and broader engineering team, taking on increasing ownership as you build depth across the platform’s AI systems.

Key Responsibilities

Contribute to the hybrid retrieval pipeline by implementing and tuning retrieval components, running experiments, and validating results with real evaluations

Build and maintain components of the agent orchestration layer, including tool integrations, prompt management, and human-in-the-loop workflows

Instrument AI and agent systems for observability (e.g., tracing model/tool calls, tracking token usage and latency, and supporting failure analysis)

Develop and maintain evaluation datasets and test suites across retrieval and agent workflows, contributing to CI-level quality gates

Support document AI capabilities, including parsing, extraction, and OCR pipelines for new client engagements

Implement per-tenant isolation checks across retrieval and agent layers to ensure no cross-tenant data leakage

Contribute to model behavior evaluation, including running prompt-injection and adversarial tests as part of ongoing evaluation efforts

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/.

3+ years of software engineering experience, with at least 1 year building LLM-powered systems (RAG pipelines, agent workflows, or fine-tuning) in a production or near-production environment

-Hands-on experience with at least one of the following:

-Retrieval-augmented generation (RAG) and reranking

-Agent orchestration with LangGraph or similar frameworks

LLM fine-tuning

-Strong proficiency in Python, including experience with async code, data pipelines, and REST APIs

-Experience with LLM evaluation methodologies (e.g., contributing to or building evaluation datasets or test suites)

-Familiarity with observability tools for LLM/agent systems (tracing, logging, monitoring model/tool calls)

-Solid understanding of modern LLM and information retrieval concepts, with the ability to discuss trade-offs -Experience with knowledge graphs or property graph query languages

-Exposure to document AI (PDF parsing, table extraction, OCR pipelines)

-Experience building evaluation datasets and labeling workflows

-Understanding of prompt injection risks and mitigation strategies in agent/retrieval systems

-Open-source contributions to LangGraph, sentence-transformers, or similar projects