Eliza

Role Description The Process & Discovery Lead will define and scale this critical function for Eliza's service offerings by identifying, structuring, and translating enterprise workflows into high-impact AI solutions. This role sits at the front of every engagement. You will work directly with executives and operators inside large organizations to uncover how work actually gets done, where value is created, and where AI can materially improve revenue, efficiency, or decision-making. You are not a consultant who writes slides. You are responsible for turning ambiguity into clear, structured AI build plans that get executed. What Youʼll Do - Process Discovery & Stakeholder Engagement - Lead structured interviews with executives and frontline operators across functions - Map end-to-end workflows, decision points, and system dependencies - Identify bottlenecks, inefficiencies, and revenue leakage - Opportunity Identification - Translate business processes into AI use cases with clear ROI - Prioritize opportunities based on impact, feasibility, and speed to value - Quantify expected outcomes (revenue lift, cost reduction, cycle time improvement) - AI Solution Design - Convert findings into structured AI project plans - Define inputs, outputs, decision logic, and system integrations - Work closely with engineering teams to ensure plans are executable - Delivery Alignment - Act as the bridge between business stakeholders and technical teams - Ensure solutions are grounded in real workflows, not theoretical use cases - Drive clarity, scope discipline, and measurable outcomes Qualifications - 5+ years experience in process improvement, operations, or transformation roles - Background in Six Sigma, Lean, or similar structured methodologies - Proven track record of delivering measurable impact in large organizations - Strong experience conducting stakeholder interviews and synthesizing insights - Ability to translate business processes into structured frameworks and execution plans - Comfortable working across business and technical teams Requirements - Experience working with or within private equity-backed companies - Exposure to digital transformation, automation, or AI initiatives - Experience in high-growth or operationally complex environments Benefits - Competitive compensation (salary + deployment bonuses or client uplift incentives) - Equity options in a growing AI services company - Flexibility to work across industries and problem domains - A collaborative, mission-driven team passionate about the real-world impact of AI

Role Description We are seeking an AI Product Manager to serve as the technical counterpart to our business development team and the owner of AI product delivery across our client portfolio. The AI PM partners closely with BD to scope and validate what we sell—then owns delivering it. This role spans ChatGPT Enterprise adoption programs and custom API/agent engagements, requiring someone who can translate between C-suite business goals and engineering constraints without pretending to be either. It’s the right role for a sharp, structured thinker who thrives on ambiguity, communicates with clarity, and knows how to get AI products across the finish line in the real world. Key Responsibilities - Business Development Partnership & Scoping - Serve as the technical counterpart to sales throughout the sales process, helping scope what is feasible, what the path to production looks like, and what a realistic engagement structure should be. - Handle the strategic and feasibility layer of technical conversations with prospects and clients: use case fit, sequencing, data requirements, timeline realism, and risk. - Know where the PM lane ends; pull in the right engineer when conversations move into deep engineering territory. - Ensure that what gets scoped and sold is what can actually be delivered, preventing commitments that do not survive contact with reality. - Use Case Discovery & Prioritization - Run structured discovery with client stakeholders within active engagements to surface AI use cases. - Build and maintain a scored use case backlog for each engagement, evaluating opportunities against feasibility, data readiness, and measurable business impact. - Make clear go/no-go recommendations on what is ready for AI and what is not. - Product Definition & Delivery - Own the end-to-end lifecycle of AI products from scoping through production launch. - Write clear product specs that translate business problems into technical requirements. - Manage the gap between demo and production: identify edge cases, compliance requirements, data quality issues, and scalability risks early. - Drive iterative development cycles, working hands-on with prompt engineering and agent design decisions alongside the technical team. - Defining Success & Measuring Outcomes - Own the definition of what success looks like for every AI deployment. - Work with client SMEs to establish domain-specific success criteria for probabilistic systems. - Track and report on product performance post-launch, including adoption, business outcomes, and continuous improvement opportunities. - Stakeholder Management - Serve as the connective tissue between business stakeholders and engineering. - Lead client-facing working sessions to align on scope, priorities, and tradeoffs. - Prepare and deliver executive-level updates on product progress, risks, and impact. - AI Center of Excellence Contribution - Contribute to repeatable playbooks for AI use case prioritization, governance, and production readiness. - Help shape the methodology for how enterprises move from AI experimentation to production at scale. - Stay current on the evolving AI platform and tooling landscape. Qualifications - 3+ years of experience in product management, technical program management, or a closely related role, with direct exposure to AI or ML products. - Working knowledge of modern AI systems—what LLMs and agents can and cannot do. - Proven ability to navigate technical conversations credibly without being an engineer. - Strong written and verbal communication skills—clear, direct, and free of jargon. - Experience managing multiple concurrent client engagements or projects without letting quality slip. Requirements - Hands-on experience with ChatGPT Enterprise, OpenAI API, Anthropic, or similar LLM platforms. - Familiarity with prompt engineering, agent design patterns, or orchestration frameworks (e.g., LangChain, LlamaIndex). - Prior consulting, professional services, or client-facing delivery experience. - Familiarity with enterprise data infrastructure, compliance considerations, or AI governance frameworks. Benefits - Competitive compensation (base salary + performance incentives tied to client outcomes). - Equity options in a growing AI services company. - Exposure to a wide range of industries and high-impact AI problems. - Travel opportunities for on-site client engagements (if desired). - A collaborative, mission-driven team passionate about the real-world impact of AI.

Role Description We are seeking a Forward Deployed Engineer (FDE) to work closely with our clients, translating complex business needs into scalable, production-ready AI solutions. As an FDE, you will serve as the technical face of our company on the ground—embedding with client teams, shaping solution architectures, and ensuring successful delivery. This role is perfect for engineers who love solving real-world problems, working directly with customers, and navigating the intersection of consulting and engineering. Key Responsibilities - Client-Facing Solution Delivery - Partner directly with client stakeholders to understand requirements, constraints, and business objectives. - Lead the technical design and hands-on implementation of custom AI systems—including model integration, data pipelines, APIs, and deployment infrastructure. - Rapidly prototype and iterate with clients in live environments. - Full-Stack AI Engineering - Build and deploy ML/AI solutions using technologies like Python, TensorFlow/PyTorch, LangChain, and cloud-native tools. - Integrate LLMs and other generative models into client products and workflows. - Support model fine-tuning, prompt engineering, and evaluation pipelines where applicable. - Cross-Functional Collaboration - Work with internal teams (product, design, research) to shape reusable components and frameworks based on deployment experiences. - Contribute client feedback and frontline insights to improve service delivery and product strategy. - Technical Advisory & Enablement - Advise client technical teams on best practices for AI/ML development and deployment. - Deliver hands-on workshops, documentation, and training to enable long-term client success. - Guide clients through infrastructure and architecture decisions (e.g., cloud, security, scalability). Qualifications - Required - 2+ years of software engineering experience, ideally in full-stack or backend-focused roles. - Hands-on experience delivering real-world ML/AI projects, either independently or in collaboration with data science teams. - Strong programming skills (Python required; familiarity with JavaScript/TypeScript, Go, or similar a plus). - Comfort with modern cloud platforms (AWS, GCP, or Azure) and CI/CD workflows. - Excellent communication and client interaction skills. - Preferred - Experience with LLMs (e.g., OpenAI, Anthropic, Cohere), vector search, or prompt engineering. - Prior consulting, professional services, or customer-facing technical roles. - Familiarity with MLOps practices and tools (e.g., MLflow, Weights & Biases, SageMaker). - Knowledge of common enterprise security, data privacy, and compliance constraints. Benefits - Competitive compensation (salary + deployment bonuses or client uplift incentives). - Equity options in a growing AI services company. - Flexibility to work across industries and problem domains. - A collaborative, mission-driven team passionate about the real-world impact of AI.