Please submit your CV in English and indicate your level of English proficiency. Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment. What this opportunity involves While each project involves unique tasks, contributors may: - Design graduate- and industry-level automotive engineering problems grounded in real practice; - Evaluate AI-generated solutions for correctness, assumptions, and engineering logic; - Validate analytical or numerical results using Python (NumPy, SciPy, Pandas); - Improve AI reasoning to align with first principles and accepted engineering standards; - Apply structured scoring criteria to assess multi-step problem solving. What we look for This opportunity is a good fit for automotive engineers with an experience in python open to part-time, non-permanent projects. Ideally, contributors will have:  - Degree in Automotive Engineering or related fields, e.g. Mechatronics, Manufacturing Engineering, Mechanical Engineering, Aerospace Engineering, etc. - 3+ years of professional automotive engineering experience - Strong written English (C1/C2) - Strong Python proficiency for numerical validation - Stable internet connection  Professional certifications (e.g., PE, CEng, PMP) and experience in international or applied projects are an advantage. How it works Apply → Pass qualification(s) → Join a project → Complete tasks → Get paid Project time expectations For this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active. Compensation On this project, contributors can earn up to $55 per hour equivalent, depending on their level and pace of contribution. Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.

Stord is The Consumer Experience Company, powering seamless checkout through delivery for today's leading brands. Stord is rapidly growing and is on track to double our revenue in the next 18 months. To meet and exceed this target, Stord is strategically scaling teams across the entire company, and seeking energetic experts to help us achieve our mission. By combining comprehensive commerce-enablement technology with high-volume fulfillment services, Stord provides brands a platform to compete with retail giants. Stord manages over $10 billion of commerce annually through its fulfillment, warehousing, transportation, and operator-built software suite including OMS, Pre- and Post-Purchase, and WMS platforms. Stord is leveling the playing field for all brands to deliver the best consumer experience at scale. With Stord, brands can increase cart conversion, improve unit economics, and drive sustained customer loyalty. Stord’s end-to-end commerce solutions combine best-in-class omnichannel fulfillment and shipping with leading technology to ensure fast shipping, reliable delivery promises, easy access to more channels, and improved margins on every order. Hundreds of leading DTC and B2B companies like AG1, True Classic, Native, Seed Health, quip, goodr, Sundays for Dogs, and more trust Stord to deliver industry-leading consumer experiences on every order. Stord is headquartered in Atlanta with facilities across the United States, Canada, and Europe. Stord is backed by top-tier investors including Kleiner Perkins, Franklin Templeton, Founders Fund, Strike Capital, Baillie Gifford, and Salesforce Ventures. Stord is building the operating system for the modern supply chain — a unified platform that powers order management, warehousing, transportation, and consumer experience for brands doing over $10B in commerce annually. Behind that platform is a large, fast-moving organization where ops teams, finance, CX, and logistics are still doing work that should not require a human. That is where you come in. As a Senior Forward Deployed Engineer on the AI Enablement team, your job is to get close to the people doing that work, understand exactly where the friction lives, and build agentic AI systems that make it disappear permanently. Not prototypes. Not internal demos. Production tools that change how Stord operates — with your fingerprints on the outcome. This role is not a traditional product engineering position. You will operate more like an embedded problem-solver than a member of a feature team — pairing engineering depth with the curiosity and judgment to identify what is actually worth building. If you have shipped internal AI tooling at scale, move fast without breaking things, and get energy from seeing the people around you work better because of what you built — this role was designed for you. Why This Role - Your users are Stord employees — you get direct, immediate feedback on what works and what doesn't - Greenfield scope: we are early in systematically automating internal workflows with AI, and you will define how it's done - High autonomy: embed, identify the problem, propose the approach, ship it — with minimal bureaucratic drag - Your work compounds: every reusable pattern and module you build makes the next automation faster - AI investment is a company-level mandate — you will have organizational support and real visibility What You'll Build This is a sample of what you'll work on — the problems will evolve as the team grows and as you find the next highest-leverage target. Tools for Internal Teams (CX, Finance, Ops, Logistics) - AI-powered tooling for Customer Experience teams — triaging issues, surfacing context, automating resolution workflows - Finance automation — reconciliation, exception handling, and reporting workflows that currently require manual effort - Ops and logistics tooling — dashboards, alerting, and intelligent interfaces that reduce the manual burden on warehouse and transportation teams - LLM-powered interfaces that let non-technical teams query, act on, and get answers from operational data without needing engineering support Workflow Automation - End-to-end automation pipelines: observe workflow → prototype → validate with domain experts → harden → ship to production - Agentic systems with proper logging, retries, monitoring, and edge case handling — not scripts that break silently - Integrations with internal systems (OMS, WMS, TMS, Billing) via APIs and event streams - Reusable automation modules that accelerate future workflow projects across the organization Developer Productivity Tooling - Internal AI-powered tools that reduce friction across the engineering development lifecycle - Lightweight APIs and integrations that connect the systems engineers rely on daily - Tooling that helps engineers at Stord write, review, and ship code faster using agentic workflows Internal Data and Analytics Products - Automated reporting and alerting that replaces manual data pulling and analysis - Dashboards and data products that surface operational intelligence to the teams who need it - Self-serve data interfaces that reduce the back-and-forth between operational teams and engineering How You Work - Embed with a team, map the workflow end-to-end, identify the highest-leverage automation target - Ship small, validate with domain experts, iterate fast — production discipline from the very first commit - Collaborate with Product Engineering when automations touch core platform systems; operate independently everywhere else - Document and publish reusable patterns so the next engineer — or the next automation — goes faster What We're Looking For Required - LLM and agentic AI development (2+ years): Proven production experience building AI agents and LLM-powered tools that automate real workflows — not toys, not demos. You have shipped them, monitored them, and fixed them when they broke. - TypeScript / Node.js (3+ years): Production backend experience. You reach for the right tool, and this is your primary one. - AI-augmented development: You use AI coding tools (Claude Code, Cursor, Codex, or equivalent) as a core part of your workflow — not occasionally, but as the reason you can move faster than a traditional engineering team. - LLM integration depth: Proven experience with OpenAI, Anthropic, or equivalent — tool use, structured outputs, prompt engineering, fallback handling, cost controls. - Embedded working style: You are comfortable sitting with non-technical teams, earning their trust quickly, and translating messy operational problems into clean engineering solutions. - API design and integration: You have built RESTful APIs from scratch and integrated with complex, sometimes poorly documented internal systems. - Observability: You instrument your systems in production. You know when something is broken before the user does. - Database: Advanced SQL with PostgreSQL. You can model data and write queries that matter. - High agency: You identify the problem worth solving, propose the approach, and drive to done with minimal direction. - Production discipline: Fast iteration does not mean fragile systems. You build things that stay running. Strongly Preferred - Experience automating workflows in operational or back-office contexts (finance, support, logistics, CX) - Vector databases and semantic search for internal knowledge retrieval - Experience building internal developer tools or platforms - Python for scripting, data wrangling, or model integration - Familiarity with Stord's stack: Elixir/Phoenix, TypeScript, Kafka, GCP Nice to Have - Workflow orchestration tools (Temporal, Prefect, Airflow, or similar) - Early-stage startup background — you have worn many hats and shipped under pressure - Domain knowledge in logistics, supply chain, or operations-heavy B2B environments - Hackathon experience or open source contributions What Success Looks Like In your first 30 days, you have embedded with at least one internal team, mapped a workflow end-to-end, and shipped something real into production. By 90 days, you have measurably reduced manual work that was previously just accepted as the cost of doing business — and people in that team can point to it. By six months, internal teams are coming to you with problems before they even think to file a ticket, you have a library of reusable patterns that others are building on, and you are the person who set the standard for how AI-powered internal tooling gets built at Stord. About Stord Stord is a cloud-based supply chain platform that enables brands to compete and grow through end-to-end logistics solutions. We process over $10B in commerce annually and operate across Order Management (OMS), Warehouse Management (WMS), Transportation Management (TMS), Consumer Experience, and Demand Planning. We are backed by leading investors and are rapidly scaling our engineering organization to match our ambitions.

Stord is The Consumer Experience Company, powering seamless checkout through delivery for today's leading brands. Stord is rapidly growing and is on track to double our revenue in the next 18 months. To meet and exceed this target, Stord is strategically scaling teams across the entire company, and seeking energetic experts to help us achieve our mission. By combining comprehensive commerce-enablement technology with high-volume fulfillment services, Stord provides brands a platform to compete with retail giants. Stord manages over $10 billion of commerce annually through its fulfillment, warehousing, transportation, and operator-built software suite including OMS, Pre- and Post-Purchase, and WMS platforms. Stord is leveling the playing field for all brands to deliver the best consumer experience at scale. With Stord, brands can increase cart conversion, improve unit economics, and drive sustained customer loyalty. Stord’s end-to-end commerce solutions combine best-in-class omnichannel fulfillment and shipping with leading technology to ensure fast shipping, reliable delivery promises, easy access to more channels, and improved margins on every order. Hundreds of leading DTC and B2B companies like AG1, True Classic, Native, Seed Health, quip, goodr, Sundays for Dogs, and more trust Stord to deliver industry-leading consumer experiences on every order. Stord is headquartered in Atlanta with facilities across the United States, Canada, and Europe. Stord is backed by top-tier investors including Kleiner Perkins, Franklin Templeton, Founders Fund, Strike Capital, Baillie Gifford, and Salesforce Ventures. Stord is building the operating system for the modern supply chain — a unified platform handling Order Management, Warehouse Management, Transportation, and Consumer Experience for brands doing over $10B in commerce annually. AI is not a future roadmap item here. It is actively reshaping how we operate — and LLM-powered features and autonomous agents are at the center of that transformation. This role is for engineers who have built and shipped AI-powered products in production — not engineers who are curious about AI. You will design and build the agent frameworks, LLM-powered features, and backend services that bring AI capabilities into daily use by hundreds of logistics operations. You will work directly with our Director of AI Products and partner with Data Scientists and ML Engineers to move fast from model to product. If you are the kind of engineer who has already shipped LLM-powered features, who gets excited about what agentic AI can do in a complex operational domain, and who wants to define the AI foundation of a platform at scale — this role was built for you. Why This Role - Direct line from your work to shipped AI features powering real logistics operations - Greenfield opportunity: you will shape how AI — including agents and LLM-powered workflows — is integrated across the platform, not inherit legacy patterns - Collaborate closely with Data Scientists and ML Engineers — this is a full-stack AI team, not siloed experimentation - Opportunity to define internal standards and tooling that other engineers build on top of - Work at a company where AI investment is a board-level mandate, not a pet project What You'll Build This is a sample of what you'll work on — the scope will evolve as we grow and as you help shape what's next. LLM-Powered Features and Agents - Conversational AI and agentic workflows for logistics operators and brand customers - LLM-powered features using OpenAI, Anthropic Claude, and Cloudflare Workers AI — with proper prompt engineering, tool use, rate limiting, fallback handling, and cost controls - Agent frameworks that orchestrate multi-step AI workflows across supply chain domains - Recommendation engines that surface actionable intelligence to operations teams Production AI Features - Demand forecasting APIs that connect ML model outputs to inventory management workflows - Intelligent routing services that leverage ML predictions for logistics optimization - Real-time anomaly detection pipelines for supply chain monitoring AI Platform Infrastructure - Fault-tolerant Node.js services that consume predictions from Modal.com, Vertex AI, and other ML platforms - Real-time data pipelines feeding ML models at production scale - Developer abstractions that make AI capabilities easy for product engineers to integrate - Caching, optimization, and serving strategies for low-latency inference - Observability, alerting, and experimentation infrastructure for AI features Cross-Functional Impact - Partner with the Director of AI Products on technical strategy and architecture decisions - Work with Data Scientists to translate model requirements into production-ready integration contracts - Support product teams in implementing AI features within their domains - Mentor other engineers on AI integration patterns and best practices What We're Looking For Required - LLM and agent development (2+ years): Proven production experience building and deploying LLM-powered features — not just API integration, but full product delivery including prompt engineering, tool use, agent orchestration, and reliability at scale. - TypeScript / Node.js (3+ years): Production experience building scalable backend services. This is your primary environment. - AI frameworks: Hands-on experience with LangChain, LangGraph, or equivalent agent orchestration frameworks. - ML platform integration: Hands-on experience consuming predictions from Modal.com, Vertex AI, or similar inference platforms. - Distributed systems: Fault tolerance, async patterns, message queues (Kafka or equivalent), event-driven architecture. - API design: RESTful and event-driven integration experience — both building and consuming. - Database: Advanced SQL with PostgreSQL. You can write a query that matters. - Cloud: Hands-on GCP, AWS, or Azure. GCP preferred given our stack. - High agency: You operate with minimal direction. You identify the right problem, propose solutions, and drive to done. - Product mindset: You optimize for user impact, not just code elegance. Reliability and delivery matter to you. Strongly Preferred - Vector databases and semantic search (Pinecone, Weaviate, pgvector, or equivalent) - Feature stores and real-time ML serving patterns - Cloudflare Workers / edge inference experience - A/B testing and experimentation infrastructure Nice to Have - Elixir / Phoenix — we run a mixed stack and cross-pollination is valued - Event sourcing patterns - Contributions to open source AI, TypeScript, or Node.js projects - Domain experience in logistics, supply chain, or operations-heavy B2B contexts What Success Looks Like In your first 30 days, you have made a meaningful contribution to production — not a small fix, but something that moves the product. You understand our stack, our AI architecture, and our roadmap, and you have already started shaping how we approach problems. By 90 days, you are a trusted technical voice on the AI team, driving architecture decisions and setting patterns that others follow. By six months, you have shipped multiple AI-powered features end to end, you are raising the bar for how AI is built and deployed at Stord, and you are actively mentoring others on what good looks like. About Stord Stord is a cloud-based supply chain platform that enables brands to compete and grow through end-to-end logistics solutions. We process over $10B in commerce annually and operate across Order Management (OMS), Warehouse Management (WMS), Transportation Management (TMS), Consumer Experience, and Demand Planning. We are backed by leading investors and are rapidly scaling our engineering organization to match our ambitions.

Lead AI & Automation Engineer - Security & Privacy (Federal Healthcare) Remote | Occasional Travel to Washington, DC Supporting Federal Healthcare Security & Privacy Programs Full-Time Salary: $145,000 - $160,000 annually (based on experience) Mission Impact This role supports modernization of security, privacy, and compliance operations within a federal healthcare environment by implementing advanced Artificial Intelligence (AI), machine learning, and automation technologies. Your work will help protect sensitive healthcare data (PII/PHI) while improving operational efficiency and enabling faster response to evolving cyber threats. Position Overview Fathom Management, Inc. is seeking a Lead AI & Automation Engineer to design and deploy AI-driven security and privacy automation solutions supporting federal healthcare programs. This role combines AI engineering, machine learning, cybersecurity analytics, and automation development to enhance security monitoring, compliance validation, and privacy operations. The ideal candidate will have hands-on experience building generative AI solutions, RAG-based chatbots, and machine learning models integrated with SIEM platforms such as Splunk. You will collaborate with security teams, compliance stakeholders, and engineering teams to develop intelligent systems that automate document review, detect security anomalies, and support responsible AI governance. Technology Stack Generative AI, Retrieval-Augmented Generation (RAG), Machine Learning, Splunk SIEM, SOAR Platforms, CI/CD Pipelines, Python, Automation Frameworks, NIST/FISMA Compliance, HIPAA Security Standards Key Responsibilities AI Engineering & Automation Development - Design and implement AI-powered automation solutions to improve security and privacy operations. - Build and manage an Agile AI development framework, including sprint planning, backlog refinement, and CI/CD pipelines. - Develop and maintain an AI-powered RAG chatbot that supports real-time security and privacy inquiries. Machine Learning & Security Analytics - Implement machine learning models within SIEM platforms (e.g., Splunk) to detect: - security anomalies - insider threats - emerging attack patterns - Deploy AI-driven analytics that improve threat detection and incident response. AI-Driven Compliance & Document Automation - Develop AI tools to automate document review and classification for PII/PHI exposure. - Build automated workflows that validate compliance with NIST, FISMA, HIPAA, and internal governance policies. - Use generative AI technologies to: - Summarize Security Incidents - Automate workflow documentation - Generate training materials - Accelerate policy and SOP creation. Responsible AI Governance - Support AI governance frameworks, including model monitoring, validation, and risk assessment. - Ensure all AI tools comply with Section 508 accessibility standards and WCAG 2.1 AA guidelines. - Develop documentation and training supporting responsible and secure AI usage in federal environments. Required Qualifications - Hands-on AI/ML engineering experience, including generative AI, RAG architectures, and predictive modeling. - Experience integrating machine learning models into SIEM or security analytics platforms such as Splunk. - Strong experience with automation engineering, CI/CD pipelines, and version control systems. - Familiarity with federal cybersecurity and privacy frameworks, including: - NIST - FISMA - HIPAA - Understanding of Section 508 accessibility standards and WCAG 2.1 AA requirements. - Strong communication and collaboration skills working with security, compliance, and engineering teams. - Experience working in regulated industries or federal environments is preferred. Minimum Requirements - Bachelor's degree in Computer Science, Engineering, Data Science, or related technical field - Minimum 5 years of professional experience in AI engineering, automation, cybersecurity analytics, or related disciplines Benefits & Career Growth At Fathom Management, Inc., we provide a comprehensive benefits package designed to support employee well-being, financial security, and professional development. Employee Benefits Include - Paid vacation, sick leave, and company holidays - Medical, dental, and vision insurance - Life insurance coverage - Short-term and long-term disability insurance - 401(k) retirement plan with company match and immediate vesting - Military leave benefits - Training and professional development opportunities - Tuition reimbursement programs - Employee wellness initiatives - Commuter benefits - Additional voluntary benefits About Fathom Management, Inc. Fathom Management, Inc. supports federal healthcare and technology modernization initiatives that improve security, privacy, and digital service delivery. Our teams specialize in AI engineering, cybersecurity analytics, digital transformation, and program delivery supporting government agencies responsible for protecting sensitive healthcare information. Joining Fathom Management means contributing to mission-critical programs that safeguard healthcare data and improve public-sector technology capabilities. Equal Employment Opportunity (EEO) Statement Fathom Management, Inc. is committed to providing equal employment opportunities to all employees and applicants. All employment decisions-including recruiting, hiring, training, promotion, compensation, benefits, and termination-are made without regard to race, color, religion, creed, national origin, sex, age, marital status, sexual orientation, gender identity, citizenship status, veteran status, disability, or any other characteristic protected by applicable federal, state, or local law.