• Identify emerging AI technologies and build Proofs of Concept (PoCs) • Test bold ideas and prove their value with data • Make high-stakes technical decisions and guide the team through ambiguity • Continuously challenge the current tech stack to ensure it fosters innovation • Partner with C-level and Product leadership to shape company strategy • Influence engineering organization to adopt new standards and technologies • Mentor Senior engineers on technical uncertainty and architectural choices

• build and optimize AI components and pipelines for Sherpany’s products • experiment with advanced AI techniques to deliver innovative features • integrate AI solutions seamlessly with product and engineering teams • ensure performance, scalability, and security in AI workflows • work with on-prem AI deployments and optimize infrastructure for reliability and compliance • stay ahead of emerging AI technologies and propose improvements • mentor junior engineers and share best practices

Supply Chain Functional AI Lead (Remote – EST) We are looking to hire a candidate with the skills sets mentioned and experience for one of our clients within the pharmaceutical Industry. This is a 6+ month contracting role, with potential for extension. This is a Remote role, with a preference for candidates in the EST zone to facilitate coordination with teams across EST, PST, and EU time zones. Role Summary: You are the AI forward-deployed engineer embedded with Supply Chain leadership - identifying, validating, building, and shipping AI capabilities that improve day-to-day operations. You translate operational problems into deployable solutions using our stack (AWS, Dataiku, Databricks, OpenAI) and partner closely with planners and supply chain leaders to drive measurable impact and ChatGPT adoption in daily workflows. A core requirement is balancing near-term value delivery with longer-term platform readiness. While the business pushes for quick wins, enterprise data and AI infrastructure will continue maturing in parallel (for example: reusable AI patterns, agent frameworks, MCP server patterns, A2A approaches, governance, and scalable integrations). You create a practical vision and execution path that connects quick wins to durable capabilities. Key Responsibilities: - Opportunity discovery & prioritization: Run process discovery with supply chain teams (planning, scheduling, inventory, procurement, logistics) to map and size AI opportunities; build a sequenced backlog tied to measurable outcomes. - Hands-on POCs to MVPs: Rapidly build POCs and evolve the best into MVPs using AWS + Databricks + Dataiku + OpenAI, integrating with enterprise data sources and real workflows. - Roadmap ownership: Produce and maintain a capability roadmap (90 days/6 months/12 months) with dependencies, data readiness needs, and adoption/change requirements. - Kinaxis-enabled use cases: Design solutions that complement and enhance Kinaxis workflows (exception management, scenario narratives, decision support, insight generation, planning explainability). - Balance quick wins vs foundations: Deliver short cycle wins that work today while shaping requirements for scalable infrastructure as IT builds out data/AI foundations (reusable components, standard integration patterns, agent orchestration approaches, monitoring/evaluation patterns). - Vision and transition plan: Define a north-star vision and pragmatic transition plan bridging today's constraints to the medium/long-term target state (platform, governance, integration patterns, reusable AI assets). - Production-minded engineering: Define architecture, evaluation metrics, guardrails, monitoring, and last-mile integration patterns; partner with platform/data teams while remaining personally hands-on. - Drive ChatGPT adoption: Build role-based prompt libraries, playbooks, templates, and enablement sessions; measure adoption and iterate based on usage and impact. - Stay current and apply responsibly: Maintain working knowledge of the rapidly evolving AI landscape (GenAI, agents, evaluation, toolchains) and translate relevant advances into practical solutions aligned to enterprise guardrails. Required Skills/Qualifications: - 8+ years of experience across supply chain analytics, digital transformation, and/or applied AI (or equivalent delivery depth). - Primary stack: AWS, Dataiku, Databricks, OpenAI, and Kinaxis in Supply Chain. - Strong hands-on build capability: Python/SQL, data modeling, rapid prototyping, and turning prototypes into usable tools. - Practical experience applying GenAI/LLMs (prompting, RAG, evaluation, guardrails, agentic workflows) to real business processes. - Experience with AWS, and at least one of Databricks or Dataiku used in delivery. - Kinaxis (RapidResponse) experience and/or supply planning integrations. - Experience with MLOps, model monitoring, and enterprise risk/controls for AI. - A clear, socialized AI opportunity map and prioritized backlog for Supply Chain. - ChatGPT adoption in supply chain routines. - Credible supply chain domain knowledge (planning, S&OP/IBP concepts, scheduling, inventory, procurement, logistics). - Proven ability to operate as a business-facing IC: ambiguity tolerance, strong writing, and demo-driven delivery. - Demonstrated ability to balance immediate impact with long-term scalability in environments where platform capabilities are evolving. - Familiarity with regulated operations and documentation controls. Other Job Details: - Job Type: C2C or W2. - Duration: 6 – 12 months with high possibility of extension. - Location: Remote (preferred candidates in the EST zone to facilitate coordination with teams across EST, PST, and EU time zones). - Pay Rate: $78/hr. on C2C. or $68/hr. on W2. - Interviews: Video interviews. - Docs required: ID proof will be required. Location REMOTE, New Jersey (Remote) Employment Type Contractor Minimum Experience Experienced

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description We are looking for an AI Native, someone who lives in Cursor, Claude Code, and Google AI Studio and treats AI as their primary teammate, not just a search tool. - This role is purpose-built for high-intensity, early-career engineers (fresh out of college or self-taught prodigies). - You will be building the "glue" that connects models, data, and systems to automate everything that isn't worth our human time. - If you’re currently using AI to 10x your own productivity and want to be paid to do the same for a high-growth startup, we want to see your GitHub. Why This Role? - Skip the "Junior" Track: We don’t care about years of experience; we care about output. You’ll be given ownership of critical workflows from Day 1. - Work with the Best: You’ll report directly to our technical leadership (Gabriele), getting a front-row seat to how a high-growth startup actually scales. Position Responsibilities - AI Orchestration: Build and maintain the "glue" between AI models and internal tools. - Rapid Prototyping: Ship 80% solutions in hours/days, not weeks. - Problem Finding: Proactively identify tasks that "aren't worth the team's time" and automate them. - Technical Querying: Handle complex data/AI queries to support leadership. Qualifications - GitHub Portfolio: Active history of commits and code quality (Mandatory). - Tool Proficiency: Expert-level use of AI coding agents (Claude, Cursor, etc.). - Background: CS or Engineering degree (or equivalent proven technical depth). - Mindset: High initiative; you do the next 3 steps before being asked. Who You Are - You are "AI Native": You’ve likely never written code without an AI agent open in another tab. - You’re a High-Velocity Learner: Maybe you just finished your degree, but you’ve already built three side projects and your GitHub is a graveyard of "weekend experiments." - Ready to Make Impact: You want to ship code that hits real customers today, not in six months. - Proactive to a Fault: You don’t wait for a “Jira ticket”; you find the friction and fix it.