Gen AI Architect

Gen AI Architect

Rosemont, IL (3days/Week)-HYBRID

Contract

Experience: -10+ Years

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

Educational Qualifications: -

• Engineering Degree BE/ME/BTech/MTech/BSc/MSc.
• Technical certification in multiple technologies is desirable.

Skills: -

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.
• Agent memory: short-term and long-term memory patterns; conversation state; summarization and context window management.
• Enterprise data access patterns for agents: retrieval/grounding strategies; context assembly from structured and unstructured sources; performance-conscious access.
• Production deployment mindset: security, reliability, monitoring, and maintainability for enterprise-grade AI services.
• Architecture & best practices: ability to design scalable components that fit into an existing framework and can be extended by the team.
• Rapid requirements intake: quickly translating ambiguous reporting/analytics asks into implementable solutions and iterating with stakeholders.
• High autonomy: tech-lead level capability without direct people management; self-directed and able to set engineering direction for the workstream