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Role: Lead AI Engineer
Location: Rosemont, IL (3days/Week) (Hybrid)
Long term Contract
Can do Only W2, No C2C
Job Description:
- We are seeking a high-Caliber AI Tech Lead / AI Engineer to design, build, and operationalize agentic AI solutions that accelerate analytics and reporting delivery.
- This role goes beyond basic agent creation and requires hands-on experience with agent orchestration, memory, and enterprise-grade data access patterns, delivering scalable components that fit into an existing framework while rapidly adapting to incoming business requests.
Responsibilities:
- Design, Architect, implement, and iterate on agentic AI solutions to shorten the cycle time for analytics, log analysis, and reporting requests.
- Design agent orchestration patterns (multi-agent workflows), tool/function calling, and memory approaches appropriate for enterprise deployments.
- Define secure and scalable data access patterns for agents (retrieval, context building, and grounding), integrating with existing data sources and governance expectations.
- Partner closely with product, analytics, and engineering stakeholders to intake requirements quickly and deliver working prototypes and production-ready solutions.
- Engineer reusable components and best practices that enable scalable delivery (not one-off scripts), aligned to an existing base framework.
- Operationalize solutions for reliability and maintainability: testing strategies, monitoring/observability, prompt/version management, and deployment automation.
- Evaluate build vs. buy options pragmatically when needed, while keeping focus on shipping solutions on the current platform stack.
Tech Stack (Core):
- Cloud: AWS (primary deployment environment; open to alternatives) Data/Analytics Platform: Databricks (including native "chat with data" capabilities and potential agent integrations)
- Agent Frameworks: LangChain, LangGraph
- Conversational analytics patterns: Ask-questions-on-data / conversational BI approaches (agent-driven analytics and dashboards
Mandatory skills:
- Demonstrated experience delivering agentic AI solutions beyond prototypes, including enterprise deployment considerations.
- Strong hands-on engineering background with AWS-based deployments.
- Experience working with modern data platforms (e.g., Databricks) and integrating LLM solutions with analytics/data ecosystems.
- Ability to operate as a senior individual contributor who can define architecture and implement key pieces end-to-end.
- Excellent communication and collaboration skills with US-based stakeholders
Skills & Expertise Needed:
- Agentic AI engineering: building and deploying LLM-powered agents for real business workflows.
- Agent orchestration: designing multi-step and/or multi-agent flows; managing tool use, control flow, retries, and failure handling.
Best Regards:
Tina
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