Solutions Architect-Gen AI

Position: Solution Architect (Generative AI) Remote Employment: Contract Job Description: We are seeking a High-Caliber Solution Architect (Generative AI) 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, Lang Graph 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. • 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 work stream