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Jobs/AI Engineer Role/Kobie Marketing - AI Engineer
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Kobie Marketing

Kobie Marketing - AI Engineer

Remote - USA2d ago
RemoteJuniorNAArtificial IntelligenceAI EngineerQA AnalystSQLMLflowPythonTeam LeadershipDockerGitB2BSnowflake

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Requirements

• 3+ years of professional Python, with production experience building and operating services • 1+ years of hands-on work with LLMs in production: prompt/context engineering, tool/function calling, structured outputs, RAG • Working knowledge of LangChain/LangGraph or a comparable framework like AgentCore Strands, CrewAI, or Semantic Kernel • Experience with LLM observability tools: Amazon CloudWatch, LangSmith, Langfuse, MLflow, or OpenTelemetry • Experience designing evaluation frameworks (MLFlow, DeepEval, LLM-as-judge, multi-turn regression) • Fluency with Git, Docker, and modern API frameworks • Clear written communication and the judgment to know when something is ready to ship • A bachelor's degree is not required. Equivalent practical experience: including bootcamps, self-taught work, career changes, or non-CS technical degrees counts. • Strongly Preferred • Hands-on experience with Amazon Bedrock and/or AgentCore as a developer: runtime, gateways, memory, policy, guardrails, observability, awscli, evaluations • Experience with Snowflake, Snowpark, or Snowflake Cortex • Fluency in writing and reading SQL, as well as understanding semantic models. • Familiarity with multi-agent patterns: supervisor/router, subagent/handoff, reflection, human-in-the-loop • A considered view on where agents should and shouldn't act and comfort pushing back when "let's add an agent" isn't the right answer • Experience in Loyalty, MarTech, AdTech, or a comparable data rich B2B domain • Who we are As a trusted partner, Kobie delivers market-leading, end-to-end loyalty solutions designed to enable customer experiences for the world's most successful brands. We do this with a strategy-led technology approach that uncovers the truth behind what drives consumers on an emotional level. We believe that our team's passion and expertise are the driving forces behind our success and are proud to be named a Top Workplaces in the USA, where the best and brightest in loyalty drive our mission of growing enterprise value through loyalty. • A place for all We celebrate and embrace diversity at Kobie! • Employment at Kobie is based solely on an individual's merit and qualifications, which are directly related to professional competence. We do not discriminate against any teammate or applicant because of race,color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy, or any other characteristic protected by applicable law. • We are fiercely committed to fostering a workplace where teammates can bring their authentic selves to work every day. Our DEI initiatives, including various committees, ensure that principles of equity, diversity, and inclusion are deeply ingrained throughout Kobie. While our leadership team fully supports our policy of nondiscrimination and equal opportunity, it is the responsibility of all teammates to uphold these values. • Ready to join us? If you’re ready to make an impact and grow in a supportive, innovative environment, we’d love to hear from you. Apply today and join the best and brightest in loyalty! • We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Responsibilities

• Agent Development • Build agent harnesses in Python using LangChain and LangGraph, including tool-calling, structured outputs (Pydantic/JSON schema), retries, streaming, and memory • Package agent harnesses for the AgentCore Runtime with appropriate context, tools, skills, and subagents that fit cleanly into production flows and scenarios • Write the tools and skills agents use API integrations, SQL queries against Snowflake, Snowflake backed knowledge retrieval with clear contracts and Pydantic validation • Evaluation and Reliability • Build evaluation harnesses (golden datasets, LLM-as-judge, regression suites) using AgentCore Evaluations, and wire them into CI • Implement guardrails around tool execution: auth scoping, input/output validation, PII and prompt-injection protections, and hallucination mitigation • You own what you ship: prototype, deploy through Amazon AgentCore, monitor traces, and fix it when it breaks • Partner with data engineers on Snowflake backed retrieval patterns (Cortex Analyst and Cortex Search Services) • Contribute to refining our internal engineering patterns as the stack evolves • Skill sets- What you need to be successful

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