Role Description We are a growing fintech organization looking to add an AI Specialist to our team! This is a distinctive role that sits at the intersection of solution architecture, client engagement, and artificial intelligence. You will be the primary AI expert within the team — responsible for both internal and external AI solutioning — working closely with clients, business stakeholders, and engineering teams to design, deliver, and continuously improve AI-powered solutions. The role is primarily client-facing and solution-oriented, drawing on the depth of a Solutions Architect, with a strong secondary responsibility for the hands-on technical delivery, optimization, and troubleshooting of AI systems. The ability to code is highly desirable: the ideal candidate can move fluidly between whiteboarding a solution with a client and diving into the pipeline to resolve a performance issue. Responsibilities - Client-Facing & Solution Leadership - Lead technical pre-sales exercises with customers, focusing on AI capabilities and use cases. - Prepare and deliver compelling technical presentations, responses, and demonstrations of AI solutions to both technical and business audiences. - Lead the design of AI solutions from conception to delivery, shaping clients’ thinking and articulating a clear path from business problem to production system. - Craft well-defined descriptions of operations and statements of work; partition solutions and support the definition of project specifications, requirements, and development needs. - Work with development teams and project managers to ensure AI solutions are delivered per the agreed scope, quality, and timelines. - Provide solutions assurance, ensuring proposals meet client business requirements and align with our technology strategy and standards. - Articulate and manage technical risks across AI engagements, including model reliability, data quality, security, and compliance considerations. - Support Episode Six’s goals and objectives including those related to sales, productivity, profitability, and industry penetration. - Assist in developing strategies and materials in support of Episode Six’s overall solution architecture practice, business development, and sales effort. - Contribute to our AI roadmap, shaping future AI solutions and capabilities. - Provide subject matter expertise on AI to clients and colleagues across the business. - Travel may be required to support client engagements. - AI Architecture & Technical Delivery - Own the design and architecture of AI solutions, including the selection and configuration of appropriate foundational models for each use case (cloud-hosted and on-premises inference). - Lead prompt engineering efforts: system prompts, tool-use definitions, multi-turn agent workflows, output parsing, and guardrail design to ensure accuracy, safety, and commercial-grade quality. - Design and implement Retrieval-Augmented Generation (RAG) architectures: document ingestion and chunking strategies, embedding models, vector databases, hybrid retrieval (dense and sparse), re-ranking, and context assembly. - Evaluate, benchmark, and continuously optimise AI solutions against defined quality metrics, including retrieval accuracy, hallucination detection, response quality, and latency. - Troubleshoot AI pipeline performance issues, identifying and resolving accuracy, reliability, and throughput problems across cloud and on-premises inference environments. - Work with internal stakeholders — engineering, security, and product — to ensure AI solutions are architecturally sound, secure, and aligned with compliance requirements (including PCI DSS and SOC 2). - Maintain deep and current knowledge of the rapidly evolving foundational model landscape, advising leadership and clients on model selection, vendor capabilities, and emerging techniques. - Build and maintain AI evaluation frameworks: automated metrics, regression testing, and continuous quality monitoring to support ongoing improvement. Qualifications - 8–10+ years of experience in customer-facing roles, solution architecture, and/or technical design, ideally within financial services or technology. - Demonstrated experience designing and deploying LLM-powered applications in production (not just prototypes). - Deep understanding of RAG architecture: document chunking strategies, embedding models, vector databases (e.g. OpenSearch, ChromaDB, Pinecone), hybrid retrieval, and re-ranking. - Proven prompt engineering capability: system prompts, tool-use definitions, output parsing, and multi-turn agent workflow design for complex, production-grade AI systems. - Strong working knowledge of foundational model ecosystems, including cloud-hosted inference (AWS Bedrock, Anthropic Claude, OpenAI, Gemini) and on-premises inference (Ollama, locally-deployed models). - Excellent communication skills (English) — ability to engage across a broad range of stakeholders at the appropriate level, whether business or technical. - Strong ability to articulate AI concepts clearly: verbally, visually, and in writing. - Experience working with APIs and cloud infrastructure, particularly AWS. - Ability to evaluate AI solution quality and drive continuous improvement through structured measurement. - Very driven and self-motivated, able to work autonomously and make decisions confidently in ambiguous situations. - A team player with a ‘can-do’, entrepreneurial attitude that thrives in an agile, ever-changing environment. Requirements - Coding ability — particularly Python — to build, prototype, debug, and optimise AI solutions directly rather than purely directing others. - FastAPI, LangChain / LangGraph, async programming, Redis integration. - Experience working with multi-model architectures spanning cloud and on-premises inference environments. - Familiarity with AI evaluation frameworks: automated metrics (Recall@5, MRR, LLM-as-judge), human evaluation protocols, and regression testing. - Experience in regulated industries, with working awareness of PCI DSS, SOC 2, and GDPR requirements as they relate to AI systems. - Knowledge of payment processing concepts: card issuance, transaction authorisation, ledger management, multi-currency operations, and the global payments landscape. - Experience with developer tooling, developer portals, or API documentation systems. - Experience with AWS services including ECS, OpenSearch Serverless, ElastiCache, Bedrock, and CloudWatch. - Familiarity with WebSocket / SSE streaming for real-time AI response delivery. - Application architecture knowledge in Java-based systems and cloud/on-premises infrastructure. Benefits - A people first mentality. - Professional development from day 1. - A 360 focus on your wellbeing. - The ability to work where you need to.

Role Description At Fetch, we’re building AI and automation systems that make our work smarter, faster, and more scalable. The AI Operations team is the human power behind that mission; ensuring our AI models, automations, and LLMs perform with quality, reliability, and impact. As an AI Operations Specialist, you’ll play a key role in maintaining the accuracy and effectiveness of Fetch’s AI systems. You’ll complete evaluations, create annotations and training data, and provide the human insight that keeps our technology aligned with real-world needs. This is a great opportunity for someone who’s naturally curious, quality-focused, and passionate about problem-solving. You’ll use tools like ChatGPT, Google App Scripts, and Airtable in your daily work; not just to save time, but to elevate your impact. This is a full-time role that can be held from one of our US offices or remotely in the United States. Responsibilities - Evaluating model outputs: Review and score LLM or automation performance to assess accuracy, consistency, and reliability. - Annotating and labeling data: Create and maintain high-quality datasets that train and improve AI models. - Applying reasoning and research: Use critical thinking, logic, and investigative research to determine the best possible answers or classifications when data is ambiguous or unclear. - Supporting SMaC (Scan, Match, & Catalog): Contribute to mapping creation, catalog support, and maintaining the quality of existing ML models that power product recognition and classification. - Using AI tools to enhance your work: Leverage tools like ChatGPT, Copilot, and other emerging technologies to increase speed and accuracy. Qualifications - Enthusiastic about Fetch: You’re excited about using AI and automation to make everyday work smarter and more rewarding. - Technically Proficient: Comfortable with Google Sheets, digital collaboration tools, and adopting new AI platforms. - A Fast Learner: You pick up new tools and concepts quickly — especially when they make you more efficient. - Adaptable to Change: You thrive in a fast-moving environment where processes evolve as we learn. - Self-Motivated: You take initiative, ask questions, and look for ways to improve outcomes and systems. - Coachable and Collaborative: You value feedback and enjoy working closely with others toward shared goals. Requirements - Hands-on experience with LLMs like ChatGPT and Gemini. - Direct experience using Google Sheets and Excel, including advanced features (pivot tables, v-look up). - Ability to research, leverage provided SOPs, and use best judgment to solve ambiguous problems. Preferred Requirements - Familiarity with data labeling, model evaluation, or QA workflows. - Experience in tech-enabled operations, automation support, or customer operations. - Background in consumer packaged goods (CPG), retail, or e-commerce. - Bonus points for SQL or Python. Compensation At Fetch, we offer competitive compensation packages including base, equity, and benefits to the exceptional folks we hire. The base salary range for this position is [$75,000 - $85,000]. Discover our benefits and how our employees live rewarded at https://fetch.com/careers .

• Scale AI Across Marketing • Design and implement AI-driven workflows that improve campaign execution, content production, and operational efficiency • Turn one-off AI experiments into scalable, repeatable systems the team can run independently • Measure the impact of AI initiatives on pipeline and team productivity, and scale what works • Lead a structured crawl-walk-run adoption model that brings the full team along • AI workflows are embedded across the marketing team and tied to measurable efficiency gains • Partner with Revops to evolve tech stack, including Marketo, Salesforce, ON24, Cvent, Qualified, and Asana • Partner with RevOps to define and standardize lifecycle stages, attribution models, and shared success metrics • Ensure marketing’s contribution to pipeline is clearly measured and communicated • Handle marketing-specific system configuration, troubleshooting, and reporting • Stay current on platform capabilities to maximize value from existing tools

• Represent the voice of industry throughout curriculum design and course development activities • Provide expert guidance on current and emerging AI applications, technologies, and workplace practices • Review and validate curriculum content to ensure relevance, accuracy, and practical value • Advise on professional AI workflows, agentic AI, governance, responsible AI adoption, and organisational implementation approaches • Translate rapidly evolving industry developments into clear learning priorities and outcomes • Contribute expertise on how professionals can apply learning directly within their own work environments • Participate in collaborative curriculum planning sessions with academic and learning design stakeholders • Challenge and refine programme content to strengthen employability, workplace relevance, and professional impact • Build consensus across diverse stakeholder groups while advocating for practical industry needs • Support the credibility and industry positioning of the programme through professional expertise and networks