Architect III - (Contract) - Remote (US - PT hours) - Possible Conversion to Perm
The ideal candidate is hands-on, pragmatic, and comfortable working in early-stage, exploratory AI initiatives where speed, iteration, and learning matter more than production hardening. Top skills include rapid AI prototyping, agent-based workflow experimentation, AWS-based GenAI services, Databricks notebook development, and strong Python/SQL.

Benefits:
Pay Range: Up to $109/hr (W2)
Work Arrangement: Fully remote
Duration: 6-month contract (strong likelihood of extension and/or conversion)

Responsibilities:

• Rapidly build and iterate AI proofs-of-concept, pilots, and demos to validate ideas, workflows, and agent-driven experiences
• Prioritize speed, usability, and measurable learning outcomes over production-grade engineering in the initial phase
• Configure and test AI agents in a controlled, repeatable way using an "agent harness" approach
• Define agent roles, prompts, tools, lightweight orchestration, and simple memory/state handling
• Run structured experiments to evaluate agent behaviors across multiple scenarios
• Tune agent configurations to improve usefulness, reliability, and clarity of outputs
• Compare different agent patterns (single-step vs multi-step flows, single-agent vs multi-agent) and capture learnings
• Use AWS cloud services to build AI-enabled experiences leveraging foundation models, agent capabilities, and knowledge retrieval integrations
• Support common GenAI use cases such as summarization, insight generation, content drafting, and workflow assistance
• Leverage Databricks for fast prototyping, lightweight data exploration, preparation, and integration into AI experiments
• Work primarily in notebooks and existing datasets to accelerate iteration speed
• Favor low-code or configuration-driven approaches (prompt templates, reusable configurations, simple orchestration patterns)
• Connect AI components across tools and APIs using lightweight orchestration patterns suitable for pilots and demos
• Partner closely with product, analytics, and business stakeholders to shape ideas, demo solutions, gather feedback, and refine concepts
• Document PoCs, agent behaviors, findings, risks, and recommendations so successful pilots can be evaluated for future scale-up

• 4+ years in AI engineering, data engineering, AI enablement, or applied technology roles with strong hands-on delivery
• Hands-on experience in AWS cloud environments, including managed GenAI/LLM services or comparable platforms
• Practical experience using Databricks for notebook-based development and prototyping
• Strong Python and SQL skills with comfort working in notebooks and lightweight scripts
• Demonstrated ability to build quick prototypes and clearly explain technical concepts to non-technical stakeholders
• Ability to work independently and move quickly in a remote, fast-paced environment

• Working familiarity with core AI/ML concepts including LLMs, embeddings, and prompt engineering
• Exposure to agent-based AI patterns, evaluation approaches, or experimentation frameworks
• Basic understanding of orchestration or automation tooling
• Prior experience supporting early-stage AI pilots, innovation programs, or rapid experimentation teams

• Deliver multiple working PoCs or pilots within the first 4-8 weeks
• Provide clear stakeholder signal on which ideas are viable and worth further investment
• Demonstrate measurable acceleration of workflows, insights, or decision-making through AI experimentation
• Produce well-documented outcomes and recommendations to support a next-phase scale-up decision