Multi-Agent/MLOps Engineer

Job Description Job Description Insight Global is seeking a Senior GenAI / Multi‑Agent Architect to design, build, and implement advanced generative AI solutions supporting commercial airline client in network planning, flight scheduling, and operational scenario analysis. This role will partner directly with IT and business stakeholders to translate operational requirements into scalable, production‑ready GenAI solutions. The ideal candidate brings deep experience in multi‑agent systems, Model Context Protocol (MCP), and AWS Bedrock, with hands‑on delivery experience across supervised agents, orchestration frameworks, and "what‑if" modeling for complex operational environments. 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.

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Skills and Requirements Business & Technical Translation:

Act as the onsite GenAI technical lead, partnering with United DT and network planning stakeholders to translate business requirements into technical architectures and agent workflows. Drive requirements intake for network planning, flight scheduling, and operational decision‑support use cases. Multi‑

Agent & MCP Architecture:

Design and implement multi‑agent systems using supervised and autonomous agents for decision support, analysis, and recommendations. Apply Model Context Protocol (MCP) to manage shared context, memory, and tool orchestration across agent workflows.

GenAI Platform & Build:

Design, build, and deploy GenAI solutions leveraging AWS Bedrock, including foundation model selection, prompt strategies, and inference optimization. Develop supervised agent layers (e.g., knowledge‑grounded chat, analytical agents, orchestration agents). Ensure solutions integrate cleanly with existing United applications, data sources, and security standards.

Use Case Delivery:

Deliver and iterate on GenAI solutions supporting: Network planning and aircraft scheduling Operational disruption scenarios Decision intelligence and recommendations Progress solutions from current‑state human‑assisted analysis to future‑state automation.

Operational Intelligence & Analytics:

Enable large‑scale summarization and insight generation (e.g., weekly global flight schedule and airline trend analyses). Design agent‑based systems capable of comparative, trend‑based, and anomaly‑driven analysis. Scenario & "What‑If"

Modeling:

Build GenAI‑enabled what‑if analysis capabilities (e.g., gate closures, aircraft changes, or operational disruptions). Integrate GenAI reasoning with supporting analytical or simulation models (e.g., Gamma or other probabilistic/optimization models) to evaluate downstream operational impact. 10+ years in AI, data, or advanced analytics roles, with significant GenAI production experience Hands‑on experience designing multi‑agent architectures Strong working knowledge of Model Context Protocol (MCP) or equivalent context/state‑management frameworks Proven experience building on AWS Bedrock Experience deploying supervised agents, orchestration layers, and tool‑using agents Strong communication skills with both technical and business stakeholders