This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description This Staff-level role shapes the foundations that determine AI quality, reliability, and impact at scale. You will architect and scale the infrastructure that powers AI quality, reliability, and reuse across Lattice. What You Will Do - Design and scale an end-to-end AI evaluation framework spanning offline evals, production tracing, and human feedback loops. - Define meaningful performance metrics (task completion, hallucination, response quality, engagement, business impact) and build the datasets and automated scoring systems that prevent regressions. - Identify and quantify the drivers of agent quality improvement and set methodological standards for evaluation across the organization. - Architect reusable agent infrastructure (multi-turn workflows, LLM DAGs, recommendation systems, standardized topologies) using LangGraph or comparable frameworks. - Build and scale RAG pipelines, vector retrieval systems, and production-grade AI infrastructure with strong reliability, observability, and performance. - Make principled build-vs-buy decisions across LLM providers, agent frameworks, and evaluation tooling, balancing capability, cost, latency, and risk. - Engineer AI systems as reusable internal platforms that multiply product engineering velocity at Lattice. - Own projects end-to-end: scope, design, execution, and delivery. - Set technical direction for agent quality and evaluation strategy across Lattice engineering teams. - Lead rigorous discussions on AI system design and evaluation methodology. - Raise the AI engineering bar through mentorship, code review, and clear technical communication across engineering and leadership. Qualifications - 8+ years of professional experience writing and maintaining production-level code, with 5+ years in designing, delivering, and operating AI/ML systems in production. - Deep production experience with LLM systems (prompting, RAG, agent orchestration, evaluation frameworks, fine-tuning). - Experience building and operating agentic systems (multi-step workflows, multi-agent topologies) and managing their failure modes. - Strong command of AI evaluation methodology and statistical experimentation. - Strong system design judgment across scalability, latency, accuracy, reliability, and cost. Requirements - Production-grade Python (clean, maintainable, testable systems). - Experience with LangGraph (or comparable agent orchestration frameworks) and LLM observability/evaluation tooling (e.g., LangSmith). - Vector databases and retrieval system design (Pinecone or similar). - Experience operating AI systems in AWS or comparable cloud environments, including CI/CD, monitoring, and deployment workflows. - Familiarity with TypeScript is a plus. - Actively engaged in AI research and industry trends. Nice to Have - Experience with RLHF, LoRA, or other model adaptation techniques. - Background in traditional ML and judgment in selecting ML vs. LLM approaches. - Experience with MLOps tooling (MLflow, DataDog). - Published research, talks, or open-source contributions in AI/ML. - Experience in HR tech or other trust-sensitive domains. Benefits - Medical insurance - Dental insurance - Vision insurance - Life, AD&D, and Disability Insurance - Emergency Weather Support - Wellness Apps - Paid Parental Leave - Paid Time off inclusive of holidays and sick time - Commuter & Parking Accounts - Lunches in the Office - Internet and Phone Stipend - 401(k) retirement plan - Financial Planning - Learning & Development Budget

About this opportunity: GoEngineer is a provider of the most compelling design platforms in the industry, deploying engineering software and 3D Printing technology to make the design process innovative, efficient, and intelligent. GoEngineer is looking for an AI Solutions and Adoption Manager to lead the identification, validation, and adoption of artificial intelligence solutions across our portfolio for our customers. The AI Solutions and Adoption Manager is the central authority on AI-enabled engineering solutions, partnering with customers, Account Executives, Solutions & Services, Sales, and Vendor Partners to move AI solutions from evaluation to successful, scalable adoption. You'll help ensure AI capabilities are practical, secure, and aligned with real-world engineering workflows—ultimately delivering measurable improvements in productivity, data quality, and product lifecycle performance. The ideal candidate will bring deep knowledge of engineering, CAD, PDM, and PLM workflows, strong technology expertise, and proven success connecting AI capabilities to customers' critical business challenges. You'll work across internal product, engineering, and sales teams, as well as external vendor partners, to assess where AI can strengthen our offerings, validate real-world use cases, and recommend strategic opportunities that move our portfolio forward. In this role, you'll build adoption roadmaps, create enablement materials, and help GoEngineer establish repeatable, scalable processes for delivering AI-enabled solutions. Your key contributions in this role will be: AI Solution Evaluation & Validation: - Research, evaluate, and validate AI solutions for engineering environments. - Connect AI capabilities to customers’ critical business challenges and validate real-world workflows to assess solution readiness. - Ensure vendor-proposed solutions meet customer requirements for usability, scalability, security, ROI, and long-term viability. AI Strategy & Market Awareness: - Maintain strong working knowledge of AI fundamentals (LLMs, generative AI, machine learning, automation) as applied to CAD, PDM, and PLM workflows. - Stay current on AI technology trends, product launches, vendor roadmaps, market adoption, competitor implementations, and emerging risks. - Participate in vendor AI training programs. Customer Adoption & Roadmapping: - Recommend appropriate AI solutions based on customer maturity, readiness, and business objectives. - Clearly communicate available tiers or levels of AI capability. - Build short-term and long-term AI adoption roadmaps aligned to customer workflows and strategic goals. Go-To-Market, Pre-Sales & Marketing Collaboration: - Support AI-related opportunities through customer meetings, demos, and technical discoveries. - Partner with marketing to create and maintain AI-focused content including web pages, roadmaps, FAQs, visuals, and comparison matrices that clearly explain available solutions. Cross-Functional & Vendor Collaboration: - Collaborate regularly with product managers responsible for CAD, PDM, PLM, and Digital Manufacturing platforms to ensure consistent AI strategy across the portfolio. - Work closely with engineering, services, sales, and vendor partners to ensure AI solutions are feasible, supportable, and scalable. Internal Enablement & Education: - Educate internal teams on AI solutions and their practical applications. - Deliver training, documentation, and best practices to enable confident positioning, scoping, and delivery of AI-enabled solutions. Governance & Responsible AI: - Ensure AI solutions align with data governance, IP protection, and access control standards. - Identify and mitigate risks related to data quality, accuracy, security, and unintended automation. We are looking for candidates with the below experience and skills, however, even if you do not meet all the listed requirements, very interested candidates should still apply: Required - 3+ years of experience in CAD, PDM, PLM, or engineering software - Understanding of engineering workflows including data translation, data management, simulation analysis, and more - Experience in pre-sales and/or implementing software solutions in customer environments. - Working knowledge of AI technologies such as LLM, Generative AI, Machine Learning, and automation as applied to structured engineering data. - Strong communication skills with engineers, IT teams, executives, and customers. Preferred - Experience working in a CAD / PLM / PDM reseller - Familiarity with engineering software ecosystems such as CAD, PDM vaults, and PLM platforms. - Experience delivering pilots, proofs-of-concept, or customer rollouts of advanced technologies. - Background in manufacturing, regulated industries, or complex product development organizations. Plus - Multi-lingual (English, French) - Knowledge of Dassault Systèmes portfolio a plus Success Measures · Successful customer adoption of AI-enabled CAD, PDM, and PLM solutions · Conversion of AI pilots into production deployments · Improved customer outcomes such as reduced cycle time, increased data reuse, and improved data quality · Strong alignment between AI offerings and engineering standards · Positive feedback from customers, sales, and engineering leadership Working Location: This role can be located in any of the GoEngineer offices in North America, or work remotely from the US or Canada. We are unable to provide employment sponsorship at this time. Competitive Compensation Includes: The annual base salary for this position is $85,000-$115,000 with a wide range to accommodate different levels of experience. More about what GoEngineer offers: At GoEngineer, we understand that our value comes from our employees, and we celebrate and respect their unique experiences. We are working to build a culture where both our employees and customers are centered in the work we do, and employees feel welcomed as they are from the first day. Generous Benefits Include: • Participation in GoEngineer’s unlimited PTO program from day one of employment. • 401(k) retirement plan with up to a 6% company match, 100% vested on day one. • Comprehensive medical coverage, including PPO and High Deductible plans with FSA/HSA options and employer HSA contributions. • Paid Family Leave, including paid pregnancy disability leave and paid parental bonding leave. • Employer paid Life Insurance policy, & Short Term, and Long Term Disability insurance, with optional supplemental coverage. • Dental and Vision insurance • Mental health, telemedicine with 24/7 access to medical providers, and wellness programs, including virtual therapy, nutrition counseling, and physical therapy. • Fertility, adoption, and family building benefits. • Employee Assistance Program (EAP) offering free, confidential counseling and support for mental health, legal, financial, and family needs. • Optional voluntary benefits, including accident insurance, hospital indemnity, critical illness coverage, identity theft protection, pet insurance, plus student loan repayment and prescription cost savings programs. To support a fair and efficient hiring process, we may use AI technology to summarize interviews and help our teams review information consistently. AI does not evaluate candidates or make hiring decisions. All decisions are made by our human hiring team.

Role Description We're looking for an AI Automations Engineer who can take ideas from concept to production and ship real automated workflows and features that users rely on. This role sits inside a cloud-based SaaS platform that has been processing over $4 billion in utility billing transactions annually for more than two decades, serving utility operators, municipalities, and energy companies across three continents. The platform is expanding and modernizing, and this role is at the center of that work. You will work across the stack with a strong emphasis on backend systems, collaborating closely with product and operations to turn ambiguous requirements into shipped functionality. Experience using Claude Code as part of your development workflow is required. This is not a narrow frontend or support role. You will build, iterate, and improve core product systems in a fast-moving environment where what you ship goes directly into the hands of real operators running real infrastructure. Qualifications - Computer Science degree or equivalent technical background - 4+ years of experience building full-stack products in a production environment - Strong experience as a backend engineer with comfort working across the full stack - Hands-on experience using Claude Code in a professional development workflow - Ability to handle light design tasks and make sensible UX decisions - Strong understanding of system design, APIs, and data modeling - Self-directed, pragmatic, and comfortable working with ambiguity in a fast-moving team Requirements - Build and maintain full-stack product features from initial idea through production - Design and implement backend systems, APIs, and data models that power billing, payments, field service, and operational workflows - Collaborate on frontend implementation and contribute to UI decisions when needed - Ensure performance, reliability, and scalability of core platform systems handling millions of transactions - Use Claude Code as a core part of your development workflow - Leverage AI tools to accelerate development, refactor code, and explore solutions - Experiment with AI-driven features, automation workflows, or internal tooling where appropriate - Help the team move faster and build smarter by integrating AI into everyday engineering work - Own backend architecture and implementation for key product areas - Work with databases, authentication, third-party integrations, and background processing systems - Write clean, maintainable, well-tested code built to handle high transaction volumes - Debug and resolve complex system issues efficiently across a mature, multi-module platform - Translate product goals and user needs into technical solutions that work in real operational environments - Collaborate with stakeholders to clarify requirements and tradeoffs - Contribute to product discussions with a builder's mindset - Improve engineering processes, tooling, and internal documentation Benefits - You will be paid in USD (bi-monthly: every 15th and 30th) - Up to 14 days of Paid Time Off annually (starting Day 1) - Observance of Holidays per company guidelines - 100% remote setup so you can work wherever you're most productive - High ownership role with real influence over product direction - Opportunity to build AI-enabled features into a platform that has been live and scaling for over 20 years - Work alongside a small, senior team that values speed and quality How to Apply Please include: - Your updated resume - A short Loom video (1 to 2 minutes) introducing yourself and describing products you have built end to end and how you use Claude Code in your development workflow - A portfolio link or links to relevant projects, repositories, or shipped products Only candidates who submit a Loom video will be moved to the next step of the hiring process. If you are an engineer who enjoys building intelligent automations into production systems, thinking deeply about workflows, and using AI as a force multiplier rather than a novelty, this role gives you the autonomy and the responsibility to build things that matter at real scale. Application Process Overview Our comprehensive selection process ensures we find the right fit for both you and our clients: - Initial Application - Submit your application and complete our prequalifying questions - Video Introduction - Record a video introduction to showcase your communication skills and work experience - Role-Specific Assessment - Complete a homework assignment tailored to the position (if applicable) - Recruitment Interview - Initial screening with our talent team - Executive Interview - Meet with senior leadership to discuss role alignment - Client Interview - Final interview with the client team you'd be supporting - Background & Reference Check - Professional reference verification - Job Offer - Successful candidates receive a formal offer to join the team Each stage is designed to evaluate your fit for the role while giving you insights into our company culture and expectations. We'll keep you informed throughout the process and provide feedback at each step.

Job Title: Generative AI Specialist - Humanities (English and Japanese) Location: Fully Remote within the U.S. (excluding California, Washington, Alaska, Colorado, Montana, New York, Puerto Rico, Nevada, Nebraska) Employment Type: Part-Time; up to 28 hours per week Who we are: Innodata (NASDAQ: INOD) is a leading data engineering company. With more than 2,000 customers and operations in 13 cities around the world, we are an AI technology solutions provider-of-choice for 4 out of 5 of the world’s biggest technology companies, as well as leading companies across financial services, insurance, technology, law, and medicine. By combining advanced machine learning and artificial intelligence (ML/AI) technologies, a global workforce of subject matter experts, and a high-security infrastructure, we’re helping usher in the promise of AI. Innodata offers a powerful combination of both digital data solutions and easy-to-use, high-quality platforms. Our global workforce includes over 7,000 employees in the United States, Canada, United Kingdom, the Philippines, India, Sri Lanka, Israel and Germany. We’re poised for a period of explosive growth over the next few years. About the Role: At Innodata, we’re partnering with the world’s leading technology companies to build the future of generative AI and large language models (LLMs). We’re on the lookout for smart, savvy, and curious Generative AI Specialist to join our global contributor community as part of our Subject Matter Expert (SME) on Demand program. This is not a traditional full-time role. It’s a part-time, remote, flexible, project-specific opportunity designed for those who want to make a real impact—on their schedule. Whether you're a writer, linguist, educator, researcher, or just deeply passionate about language and logic, this role lets you contribute to cutting-edge AI development while maintaining control over your time. You’ll be helping LLMs learn the intricacies of language and reasoning—not just how to write, but how to think. If you’ve ever dreamed of shaping the intelligence behind tomorrow’s technology, this is your chance. This is more than just a gig—it’s a rare chance to help shape the future of AI from anywhere in the world, on your own terms. What You’ll Be Doing: Core tasks would include (any/multiple of) but not limited to the following: - Evaluation: Rating/assessing the performance of AI models or algorithms based on their output or behavior through a set of evaluative questions. - Annotation Labeling: Labeling elements of a piece of content rather than the content as a whole. - Classification: Assigning predefined categories or labels to items. - Content Quality: Evaluating the perceived quality and/or appropriateness of content - Content Understanding: Generating labels to advance understanding of a concept, trend etc. - Data Augmentation: Creation of additional training data for machine learning models by applying transformations to the original data, such as modifying images (rotation, flipping, cropping), generating new text (paraphrasing, summarization), or altering audio/video signals (speed modification, pitch shifting) to reduce overfitting and increase dataset diversity. - Grading: Reviewing data and identifying whether or not a product feature works as intended based on the project's guidelines. - Identification Labeling: Labeling model outputs to identify if a piece of content is or isn't something. Examples: identify clickbait; identifying gaming videos; identifying branded content. - Preference Ranking: Ordering or ranking items based on a set of preferences or criteria. - Prompt Generation: Creating prompts or questions that will be used to generate responses from a language model or other AI system. - Relevance Evaluation: Projects that evaluate the relevance of content based on a relevancy scale (1-3, 1-5, etc.). - Response Generation: Generating responses to prompts or questions using a language model or other AI system. - Response Rewrite: Rewriting existing text while preserving the original meaning, often to improve clarity or style and adherence to guidelines. - Response Summarization: Producing concise summaries of longer pieces of text or data. - Similarity Evaluation: Projects where content is compared in order to drive a determination. - Transcription: Converting spoken language or audio content into written text. - Translation: Converting text or spoken language from one language to another. - Data Collection: Gathering and compiling various forms of data to be used for training, evaluating, or fine-tuning the AI models. This may include text, images, videos, audio files, or other types of digital content. Minimum Qualifications: - A Bachelor’s degree or higher in a humanities specialization is required. Advanced degrees are strongly preferred (Master’s or PhD) - Professional or Expert level proficiency (C1/C2) in English and Japanese Salary rates at Innodata vary depending on a wide array of factors, which may include but are not limited to the role, skill set, educational background and geographic location. Innodata is an equal opportunity employer and values diversity. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity or expression, sexual orientation, age, marital status, veteran status, disability status, or any other legally protected status. Innodata is committed to creating an inclusive environment for all employees and applicants. If you need assistance or accommodation during the application or recruitment process due to a disability, please contact us and we will be happy to assist. Applicants must be legally authorized to work in the United States at the time of hire. Innodata is unable to provide visa sponsorship now or in the future for this position. Please be aware of recruitment scams involving individuals or organizations falsely claiming to represent employers. Innodata will never ask for payment, banking details, or sensitive personal information during the application process. To learn more on how to recognize job scams, please visit the Federal Trade Commission’s guide at https://consumer.ftc.gov/articles/job-scams. If you believe you’ve been targeted by a recruitment scam, please report it to Innodata at verifyjoboffer@innodata.com and consider reporting it to the FTC at ReportFraud.ftc.gov.