At Qohash, we're building a foundational pillar of Canada's digital sovereignty. As AI adoption accelerates and data becomes a strategic national asset, we believe security must scale differently, without moving or copying data.

We seek bold, mission-driven individuals energized by meaningful impact, not incremental change. You thrive in high-stakes, fast-moving environments where policy, technology, and global expansion converge. You take ownership, embrace constructive conflict, and act with accountability even when the path isn’t fully defined.

We value people who combine technical depth with strategic clarity, leaders who pursue excellence, show resilience under pressure, and collaborate across disciplines to protect the world’s most sensitive data.

If you’re motivated to help build a sovereign, globally respected technology champion, read on.

Company culture is at our core

Our 5 core values are more than just words; they are a way of life for us. We know that companies with a strong culture and a higher purpose perform better in the long run.

Do our values speak to you?

• Pursuit of excellence - Data security companies that aren’t constantly improving every aspect of what they mean by ‘excellent’ shouldn’t exist.
• Resilience - Security is a marathon without a finish line. Our customers and employees must have the support they need.
• Mission focus - We are here to protect the world’s most sensitive data and create a safer digital future for all.
• Accountability - Trust is earned through actions, not blame or wishful thinking. Fulfill promises and take responsibility for mistakes.
• Embracing conflict - To reach consensus and problem-solve quickly, it’s important to communicate honestly and courageously.

Who you are

You’re an AI-native Full Stack Developer who leverages LLMs and AI coding tools as a core part of your daily workflow, not as an occasional aid, but as a force multiplier. You bring strong engineering fundamentals in Java/Kotlin and React, and you’re energized by the speed that AI-assisted development unlocks. You thrive in fast-paced, high-accountability environments and treat quality, security, and velocity as inseparable goals.

What you will do

• Analyze, design, and implement features.
• Develop Microservice Oriented Architecture & build reusable components.
• Write well-designed, efficient, and testable code, using AI coding tools to accelerate implementation while maintaining code quality standards and performing unit and integration tests.
• Analyze performance and reliability to ensure that data is moving fast and accurately.
• Perform identification of code metrics and necessary analysis (code, requirements, system risk, and software reliability).
• Correct anomalies and problems as they arise.
• Test the implemented features to make sure all acceptance criteria are met
• Review code and provide guidance to other engineers to ensure that software is developed with maintainability, performance and security in mind.
• Participate in projects from the initial idea to launch.
• Advise the product owner on technological choices and decisions concerning developments.
• Contribute to the continuous improvement of development velocity, including AI-assisted testing, automated deployment pipelines, and LLM-augmented code review practices.
• Review the security/reliability implications of software design decisions.
• Collaborate with the security team to integrate security best practices into software development processes.
• Communicate risks associated to any activity, technology or processes as you identify them
• Participate in incident response activities and work with the infrastructure and security teams to investigate and remediate incidents.

What your resume shows

Must Haves

• 5+ years experience with Javascript Frameworks (React and Typescript)
• 5+ years of experience in Microservices development with Kotlin or Java, Springboot
• Demonstrated daily use of AI coding assistants (e.g., GitHub Copilot, Cursor, or equivalent) to accelerate development, with the ability to critically evaluate, refactor, and own AI-generated code
• Proven ability to operate within Agile/Scrum delivery cycles, using AI tools to compress sprint velocity and maintain documentation quality without adding overhead

Nice to Haves

• Preference is for candidates resident in Quebec
• Experience working in a Startup environment
• Cloud (AWS or Azure) experience
• Experience with Cybersecurity
• Bilingual in English and French
  
  

What’s in it for you?

• Competitive salary range.
• Enjoy up to six weeks of paid time off annually, because we value your work-life balance.
• Comprehensive health benefits, including:
  • Life insurance
  • Short- and long-term disability
  • Paramedical and telemedicine services
  • Health Spending Account (HSA)

Qohash is an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, colour, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by applicable law. A working proficiency in English is required for this position based on the company's operational requirements. Only those candidates selected for interview will be contacted.

About the role

We’re looking for an AI Marketing Specialist to scale and optimize our marketing efforts using AI. You won’t just be using AI tools; you will be building autonomous agentic workflows that bridge the gap between "AI potential" and "operational reality." Your goal is to transform our email operations, content pipelines, and campaign execution from manual, rule-based processes into intelligent, self-optimizing agentic systems. You’ll work with Marketing and Product teams across channels such as social media, email, affiliates, and product launches, supporting AI-powered multi-channel workflows and strategies that increase engagement, awareness, and conversions.

What You’ll Do

• Architecting Agentic Workflows: Design, deploy, and iterate on multi-agent systems to automate end-to-end marketing processes (e.g., dynamic content creation, social strategy, automated partnership ecosystems, and personalized email sequencing).
• Email Operations at Scale: Move beyond traditional email "blasts." Build and manage agent-driven email frameworks that autonomously segment, personalize, A/B test, and optimize send times based on real-time engagement data.
• Content Supply Chain: Develop AI-powered pipelines that take a core strategic asset and autonomously adapt it into dozens of formats (blogs, social snippets, ad copy, email nurture streams) while maintaining strict brand guardrails.
• Orchestration & Governance: Define the "human-in-the-loop" (HITL) protocols. Build the monitoring systems that ensure agentic workflows remain accurate and brand-compliant.
• Tech Stack Integration: Develop deep, bi-directional integrations between AI agents and our core toolkit to create a unified, agent-driven marketing nervous system.
• Continuous Optimization: Establish KPIs for AI agents. Monitor for latency, cost, and output quality, continuously refining prompts and model logic to improve performance over time.

What You’ll Need

• "Builder" Mindset: You don't just "use" AI - you build with it. You are comfortable mapping a 10-step human process into a logical, automated sequence of tool calls and reasoning steps.
• Technical Fluency: You have practical experience with AI orchestration tools (e.g., n8n, LangChain, Make.com, or platform-native AI agents) and are comfortable working with LLM APIs and prompt engineering.
• Marketing Ops Depth: You understand the lifecycle of a customer, attribution modeling, and the nuances of high-volume email deliverability and CRM data hygiene (Salesforce/HubSpot).
• Systems Thinker: You can distinguish between deterministic automation (if this, then that) and probabilistic agentic behavior (set a goal, figure out the best route to achieve it).
• Communication: You can explain technical AI concepts to non-technical stakeholders, ensuring trust and alignment across the marketing and sales teams.
• Hands-on experience with AI content generation, using AI tools and AI agents to improve workflows and output, and workflow automation.
• 3+ years in Marketing Operations, Growth Engineering, or GTM Systems.
• Proven track record of shipping automations that measurably improved efficiency or conversion.
• Deep curiosity about the evolving AI landscape; you are likely already testing agentic frameworks in your own time

Engineering at Brex

Engineering at Brex is about building systems that scale with speed and intention. Our teams span Software, Data, Security, and IT, and operate with high autonomy and deep collaboration. We tackle hard technical problems, own our outcomes, and push for excellence at every level — from architecture to deployment. It’s an environment where engineering is a craft, and builders become leaders.

What you’ll do

As an Application Security Engineer, you will contribute to finding and responding to security vulnerabilities across the Brex platform. In this role, you will participate in code reviews, design reviews, penetration testing, and vulnerability management. You will contribute to tooling that performs static and dynamic testing of the Brex platform and supports secure developer workflows. Application Security is part of our wider Financial Scale organization, which means you will work closely with Security Operations, GRC, Product Security, Front End Platform, and IT Infrastructure teams.

We're looking for individuals with a solid foundation in penetration testing and a curiosity for finding vulnerabilities in complex systems. You should have experience identifying and documenting vulnerabilities across common vulnerability classes and be able to communicate their risk clearly to engineering and product teams. This role is highly cross-functional — you'll have the opportunity to collaborate with engineering teams across Brex and grow your security expertise in a fast-moving environment.

Brex is pioneering the next wave of AI-driven financial services for dynamic, high-impact companies like Coinbase, Robinhood, and Anthropic. As we integrate AI across our product suite, this role will give you hands-on experience contributing to AI security at Brex. You'll apply emerging AI security best practices to help secure our agentic features, identify attack surfaces introduced by LLM-powered systems, and partner with product and engineering teams to build AI capabilities our customers can trust with their critical financial operations.

Responsibilities

• Identify vulnerabilities across common vulnerability classes (e.g., OWASP Top 10), document findings clearly, and communicate risk to drive remediation efforts
• Participate in penetration testing and design reviews alongside senior engineers, contributing to the identification of vulnerabilities and insecure designs
• Contribute to internal tooling and automation efforts that support SAST and DAST testing of the Brex platform and promote secure development practices
• Collaborate with engineering and product teams to support the design of secure product features
• Actively contribute to a culture of security awareness through knowledge sharing and peer learning

Requirements

• 4+ years of work experience in Application Security or a related role
• Demonstrated ability to find and document vulnerabilities in complex systems, with clear communication of business risk
• Hands-on experience with a subset of secure development activities, such as code review, threat modeling, or penetration testing
• Experience identifying security risks in AI/ML systems — such as prompt injection, model manipulation, or data poisoning — through work experience, personal projects, CTFs, or bug bounties
• Familiarity with agentic workflows and the ability to reason about attack surfaces introduced by LLM-powered features
• Knowledge of Python or scripting languages to automate tasks and build tooling
• Collaborative mindset paired with strong written and verbal communication skills

Bonus points

• Experience with Kotlin, gRPC, GraphQL, Kubernetes
• Previous experience as a software engineer
• Experience with securing distributed systems in AWS and cloud environments
• Experience with web application security reviews
• Contributions to the wider technical community — open source, public research, CTF participation, blogging, CVEs, or presentations
• Experience submitting to bug bounty or responsible disclosure programs
• Published AI security research or contributions to AI security frameworks

Compensation

The expected salary range for this role is $152,000 - $190,000. However, the starting base pay will depend on a number of factors including the candidate’s location, skills, experience, market demands, and internal pay parity. Depending on the position offered, equity and other forms of compensation may be provided as part of a total compensation package.

Brex LLC is a wholly owned subsidiary of Capital One, N.A.

Why this role exists:

We are growing our AI team and are looking for a Senior AI / Generative AI Engineer to build and operate production-grade LLM-based systems across the platform.

This role focuses on applied Generative AI: internal AI automation, chatbots, AI assistants, and MCP-based services already used in production. You will work on top of an existing ML and data platform, building systems that are reliable, maintainable, and practical to operate.

This is a hands-on engineering role with end-to-end ownership. Not research. Not prompt-only.

What you’ll drive:

Technical Ownership

• Own LLM-based systems from design to production support.
• Design architectures for Generative AI systems (RAG, agents, tool/context serving).
• Make clear trade-offs between quality, latency, cost, and complexity.
• Set engineering standards for building and operating AI systems in production.
• Act as a technical reference point for applied GenAI.

Hands-on AI Engineering

• Build and maintain production LLM-powered systems.
• Develop chatbots and AI assistants with predictable behavior.
• Design and implement RAG pipelines (ingestion, embeddings, retrieval, generation).
• Implement agent-style workflows with tool/function calling.
• Build and integrate MCP servers or similar context/tool-serving components.
• Integrate AI systems with backend services and ML infrastructure.

Production & Reliability

• Design evaluation frameworks for LLM outputs.
• Monitor LLM behavior, system health, and costs in production.
• Address performance, scalability, and operational issues.
• Handle production incidents and contribute to long-term fixes.
• Design systems with failure modes, fallbacks, and graceful degradation.

What makes you a GR8 fit

Must-have

• Strong software engineering background.
• Proven experience building LLM-based systems in production.
• Hands-on experience with: LLMs and RAG architectures, Chatbots or conversational AI systems, Tool/function calling and agent-style patterns.
• Experience with context or tool-serving systems (MCP or similar).
• Experience integrating AI into real-time production products.
• Understanding of performance, scalability, and cost trade-offs.
• Cloud experience (preferably AWS).
• Strong engineering fundamentals (testing, debugging, reviews, observability).

Nice-to-have

• Multi-agent or workflow-based systems.
• Fine-tuning or adapting open-source LLMs.
• ML platforms / MLOps background.
• Experience operating latency- or cost-sensitive systems.
• Production incident ownership in AI systems.

Tech Stack:

• Languages: Python, SQL.
• LLMs: Amazon Bedrock, OpenAI, Anthropic, open-source models.
• Frameworks: LangChain, LangGraph, Pydantic, Langfuse.
• RAG: Embeddings, Qdrant / FAISS / OpenSearch / pgvector.
• Cloud: AWS (ECS / EKS / Lambda, S3, OpenSearch).
• DevOps: Docker, Git, CI/CD.

What You'll Be Doing:

• Work directly on building, deploying, and iterating on machine learning models and agentic workflow features that address real customer needs
• Apply ML techniques to improve accuracy and overall system performance, ensuring solutions are robust, reliable, and production-ready for customers
• Improve, implement, and validate ML models and agentic workflows supporting submission intake, underwriting decision-making, and automation tasks
• Deploy and adapt autonomous agent behaviors into customer-specific workflows, translating core AI capabilities into practical solutions
• Develop and maintain evaluation pipelines, monitoring systems, and performance metrics to ensure reliability under evolving production conditions
• Monitor production systems via logs, metrics, and user feedback to diagnose issues, debug failures, and drive resolution
• Take end-to-end ownership of problems — implementing fixes or coordinating with engineering and infrastructure teams as needed
• Partner closely with Data Science and Engineering teams to iterate quickly and deliver high-impact solutions

Who We Hope You Are:

• Bachelor's or master’s degree in Mathematics, Operations Research, Data Science, Artificial Intelligence, or a related field with foundational knowledge in machine learning, deep learning, and natural language processing.
• Experience working in a fast-paced, cross-functional environment
• 2+ years of experience as a Machine Learning Engineer, Applied Scientist, or similar role delivering ML solutions in production
• Experience working directly with customers or stakeholders to translate business needs into technical solutions
• Hands-on experience adapting, extending, and deploying ML/LLM systems (including agentic workflows and prompt engineering) in real-world use cases
• Strong experience with experimentation, evaluation, and monitoring pipelines, including analyzing production logs and debugging systems
• Experience deploying and iterating on ML systems in cloud environments in collaboration with engineering teams
• Proven track record of ownership — driving issues through to resolution in production systems

Base Salary Range: $155,000 - $180,000
Final offer amounts are determined by multiple factors including candidate location, experience and expertise and may vary from the amounts listed above. Total compensation package also includes bonus, stock options, benefits and additional perks. 

NEAR is one of the most active ecosystems in crypto, spanning a Layer-1 protocol, a leading cross-chain intents and settlement layer (NEAR Intents), a consumer-facing financial app (near.com), and a rapidly growing AI stack & agent framework (Ironclaw). It also sits at a turning point on security. Recent industry incidents, the acceleration of AI-enabled attacks, and the emergence of institutional counterparties now requiring a named security owner have made it clear: the ecosystem needs a senior, credible operator to own this function end-to-end.

This is that role. You will be Head of Security, with primary ownership of Defuse Labs (NEAR Intents) and NEAR One — the two entities carrying the highest operational risk — and extending coverage to the NEAR Foundation and NEAR AI in partnership with their leadership. A formal Security Committee provides oversight and governance; you provide execution.

What you'll own

Your objective is to pragmatically manage hard security risks across companies operating complex financial instruments in adversarial cross-chain environments. We care about real practical security first and foremost, not paper-based certifications.

You will be protecting against state actors, insider threats, and countless numbers of LLM agents. The scope includes every single chain we integrate. Think defence in depth, but the depth must cover things like 13-block reorgs of Litecoin or margin trading engine exploits in a partner protocol.

End-to-end security posture
Define and operate security across NEAR Intents and NEAR One — including identity, cloud (AWS/GCP), endpoints, application security, and SecOps — within a crypto-native model where smart contract risk, on-chain monitoring, key management, and validator/infrastructure security are first-class concerns.

Smart contract and protocol security
Establish security standards, audit strategy, and release gating for production deployments. Own how code moves from development to mainnet.

Incident response
Lead ecosystem-wide response across both traditional infrastructure and on-chain events — preparation, detection, containment, and recovery. When incidents happen, you are the point of coordination and decision-making.

Key management and asset security
Design and oversee key management architecture across protocol, treasury, and operational environments, including MPC, custody models, and access controls.

Offensive security
Define and run a continuous testing strategy — internal security testing, external audits, red teaming, and bug bounty programs.

Team and tooling
Build a lean, high-leverage security function from the ground up. Decide where commercial tooling is required and where open-source or in-house approaches are more effective.

Governance and external engagement
Serve as a voting member of the NEAR Security Committee. Act as the primary security counterpart for institutional partners, auditors, and regulators. Work closely with Legal on disclosures, regulatory matters, and enforcement coordination. Collaborate with external advisors, including SVRN.

AI and emerging surfaces
Establish security practices for AI and agent-based systems, including model integrity, prompt injection risks, and agent execution boundaries.

Who you are

• A proven security leader from an environment where getting it wrong was not an option — a major on-chain protocol, a top-tier exchange or custodian, critical infrastructure, or a peer ecosystem operating at serious scale. You've built programs, not just maintained them.
• Deeply technical. You can read a Terraform module, challenge a threat model, and set budget priorities in the same afternoon — and you're comfortable arguing with engineers on the merits.
• Think from first principles. You understand how ROI on an audit is calculated and how much of the cost is attributable to the auditing company brand alone. You understand what formal verification is, what risks it protects against and how and why it fails. 
• You are excellent at system design. You understand how to isolate risks and limit blast radius. You’ve designed circuit breakers before. You understand how to divide and conquer projects quickly where getting results would normally take years.
• Fluent in crypto risk, or demonstrably capable of becoming so quickly. Smart contracts, on-chain forensics, MPC, key management, and validator security are core to this role. If you treat crypto as "just another vertical," this isn't the right fit. You know what https://rekt.news/ is and you know the most common hacks of the lending protocols.
• Clear authority, used well. You have a direct mandate from the Security Committee and real authority over security for the entities in your remit. You know when to enforce and when to persuade — and you're not afraid of either.
• Composed in public. Incident disclosures, partner calls, committee and board reporting — this role lives in the open.

Founding CTO at Redbolt.ai 

Redbolt AI is the security and reliability layer for in-production AI systems. It’s the commercial open core evolution of NVIDIA's open source red-teaming framework, garak, and NeMo Guardrails. Redbolt builds on trusted open source technology and adds the security layer that empowers users to deploy AI at scale.

We're looking for a Founding CTO to build Redbolt into an era-defining AI technology. As the founding CTO, you’ll define initial product vision, build commercial features and an engineering team to accelerate product velocity, get closer to customers, and deepen open-source contributions to NVIDIA's Garak. 

The opportunity

The market for AI security is early but moving fast. The risks of unguarded AI systems are well-known but the infrastructure to protect against these risks don’t really exist yet.

Redbolt starts with a meaningful foundation: NVIDIA's open-source tools already have community traction and credibility. Your job is to turn that into a product and company that enterprises depend on.

If you've been looking for the right moment to build something that matters, this is it.

The role

As the technical founder, you will: 

• Defining the vision. What should this company become? What's the product roadmap that turns open-source adoption into a billion-dollar enterprise business? You'll own that strategy.
• Building the foundation. You're writing code, shipping product, and making architectural decisions that will compound for years.
• Hiring the team. You'll recruit and lead the engineers who build Redbolt alongside you.
• Partner with a CEO. Once there's traction, OCV will lead a search for a co-founder CEO to partner with you - someone to own go-to-market, fundraising, and business operations while you own product and engineering. You'll be deeply involved in selecting that person.

About you 

You're a deep technical expert in LLM security, ML engineering, or adjacent infrastructure. You understand how these systems fail and how to prevent them.

You've operated at a high level technically: staff/principal engineer, engineering lead, or founded something yourself.

You're entrepreneurial. You've been waiting for the right opportunity to build something from the ground up, with real support and resources behind you.

You have conviction about the AI security space. You've thought about what needs to exist and have opinions about how to build it.

About Open Core Ventures

"As software has eaten the world, open source is eating software." — Peter Levine

Commercial open source software companies have captured hundreds of billions in enterprise value—yet this represents only a fraction of the trillions delivered by OSS today. We're still in the early innings.

GitLab co-founder and executive chair Sid Sijbrandij started Open Core Ventures (OCV) to accelerate this opportunity. We start companies around promising open source projects—the same approach that took GitLab from OSS project to IPO in seven years.

We recruit founders and help them reach escape velocity. We’ve started 30+ companies around open source projects, including Fleet, FlowFuse, and Mermaid Chart. 

You can read more about our approach in our public handbook.

🚀 Hermes Web: Call for Founding Engineer

Hermes Web is looking for a founding engineer to build the first polished, hosted personal AI agent product.

Some facts about us:

• Incubated by Open Core Ventures, the studio founded by Sid Sijbrandij (ex-CEO of GitLab)
• Building the hosted, non-technical-user version of Hermes Agent — the fastest-growing open-source agent framework after OpenClaw
• OCV underwrites infrastructure and LLM costs, so you optimize for growth and polish, not unit economics
• Fully remote, product-focused, compressed sprint cadence

If you want to own product and engineering end-to-end, ship consumer-grade polish in a space that's still raw, and help define what a mainstream AI agent product looks like, this is for you.

Project described below.

Requirements

• High agency, ship fast without hand-holding
• Strong Python skills — FastAPI or similar production web framework experience required
• Strong frontend skills (React, Next.js, TypeScript) for the chat, memory, and activity surfaces
• Experience with auth, billing, and multi-tenancy in production products
• Container orchestration experience (Kubernetes, Nomad, ECS, or equivalent)
• Experience with AI-native tools (Cursor, Claude Code, model APIs)
• Knowledge of agents, LLM gateways, rate limiting, and abuse prevention
• Comfortable working across frontend, backend, infrastructure, and AI workflows

The kind of person we want: someone who has shipped a consumer or prosumer product they're still proud of, and who responds to an aggressive timeline with "tight but doable if we cut X, Y, Z" rather than "let me spec it first."

Bonus skills:

• Experience with agent frameworks (Hermes, OpenClaw, LangGraph)
• LLM gateway or proxy work
• Stripe subscription billing at scale
• Production experience hardening agentically-generated code
• OSS contributions
• Consumer AI product experience (Cowork, Cursor, or similar)

Project: Hosted Hermes Agent Platform

1. Introduction

We are building a multi-tenant hosted platform that gives anyone their own personal Hermes agent running in the cloud in under 60 seconds. No terminal, no API keys, no configuration. The agent persists, remembers them, and gets better over time.

This project includes:

• Per-user Hermes containers with network and storage isolation
• A warm pool provisioning system for instant signup-to-first-message
• A production-hardened chat, memory, and activity interface
• An LLM gateway that meters usage, enforces caps, and prevents abuse
• Bundled Claude Sonnet access — users never see an API key or model selector
• Stripe billing infrastructure and self-serve subscription flows

2. Requirements

Platform and provisioning

• Per-tenant container orchestration via Kubernetes or Nomad
• Warm pool pattern for sub-90-second provisioning
• Idle sleep and fast wake (under 2 seconds on incoming message)
• Persistent per-tenant memory and conversation storage
• Auth via Clerk or Auth0 (email + Google OAuth, email verification required)

Frontend

• React, Next.js, TypeScript, Tailwind, shadcn
• Multi-tenant chat, memory, and activity surfaces
• Graceful handling of connection loss, agent timeouts, container restarts
• Streaming responses, conversation history, new-thread flows

LLM gateway

• Proxy every Anthropic API call from every tenant container
• Hold Anthropic API keys server-side; tenant containers never see them
• Per-tenant metering with second-by-second granularity
• Hard daily and monthly cost caps
• Circuit breakers for runaway loops
• Ops kill switch for any tenant

Billing and ops

• Stripe subscription integration at $20/mo
• Self-serve upgrade, downgrade, cancel
• Internal ops dashboard for user management and anomaly response
• Runbooks for common failure modes

3. Non-Goals

• Developer-facing platform
• Self-hosted desktop or mobile apps
• Skills marketplace or plugin ecosystem
• Workflow builder, triggers, scheduled agents
• Team accounts, SSO, enterprise features
• Multiple LLM providers or model selection
• Bring-your-own API key
• Forking Hermes — we track upstream and contribute back

4. Prior Art

• Hermes Agent — the open-source framework we build the hosted experience on top of
• OpenClaw — the largest agent framework today and reference for community patterns and growth dynamics
• LangGraph Deep Agents — architecture patterns for stateful long-running agent workflows
• Anthropic MCP — server design patterns for tool interfaces and permission-aware context
• Cowork (Anthropic) — polish bar and UX patterns for non-technical AI agent products
• Cursor agent UI — interaction model for AI agents in consumer products

Growe is a leading business advisory and services group in iGaming and Entertainment. We are creators of strategies that work and solutions that scale. Combining strategic vision with hands-on expertise, we help businesses navigate the fast-evolving industry, seize new opportunities, enter new markets, and achieve sustainable growth.

Our expertise spans across key areas: from business and brand strategy development to market research, marketing solutions, IT customization, organizational structuring, and talent management. We partner with our clients to turn challenges into competitive advantages, ensuring successful market entries and long-term global expansion.

At Growe, there are no limits to our ambitions! We boldly break stereotypes and strive for unparalleled achievements in an ever-changing industry. 

Are you ready to grow with us?

Growe welcomes those who are excited to:

• Define and drive the company-wide AI strategy, identifying key opportunities for AI transformation across products, engineering, and operations;

• Develop and maintain the AI adoption roadmap, including the selection of AI technologies, tools, and platforms;

• Integrate AI solutions into company processes, including software development, data analysis, QA/testing, documentation, and customer support workflows;

• Build and support internal platforms and tools that enable teams to effectively leverage AI capabilities;

• Collaborate with engineering, analytics, and product teams to identify and implement practical AI use cases;

• Lead internal AI initiatives, including experimentation, proof-of-concept projects, and rapid evaluation of emerging AI tools;

• Educate and support teams in adopting AI tools and best practices through workshops, training sessions, and internal knowledge sharing;

• Promote and develop a strong AI-driven culture across the organization;

• Provide internal AI consulting to business units, helping identify opportunities and evaluate the potential ROI of AI initiatives.

We need your professional experience:

• 8+ years of experience in technology companies, preferably in software engineering, platform engineering, or data/AI-related roles;

• Proven experience implementing new technologies and driving technical transformations at an organizational level;

• Hands-on experience working with modern AI technologies and ecosystems, including LLM-based tools and AI-powered workflows;

• Strong understanding of AI solution architecture and integration of AI tools into developer workflows;

• Experience leading process improvements or transformations in engineering teams;

• English - upper-intermediate or higher (able to communicate in technical discussions);

• Experience implementing AI coding assistants or AI tools for developer productivity (will be a plus);

• Experience working with AI agents or agent-based systems (will be a plus);

• Experience building internal developer platforms or engineering productivity tools (will be a plus);

• Experience working with data platforms or ML infrastructure (will be a plus).

We appreciate if you have those personal features:

• Strategic thinking and the ability to identify high-impact AI opportunities;

• Strong problem-solving and experimentation mindset;

• Strong communication skills and the ability to explain complex technical concepts in a clear and accessible way;

• Ability to influence teams and drive change without direct managerial authority;

• Curiosity and passion for emerging technologies and innovation;

• Ability to balance long-term strategy with fast experimentation and practical delivery.

We are seeking those who align with our core values:

• GROWE TOGETHER: Our team is our main asset. We work together and support each other to achieve our common goals;

• DRIVE RESULT OVER PROCESS: We set ambitious, clear, measurable goals in line with our strategy and driving Growe to success;

• BE READY FOR CHANGE: We see challenges as opportunities to grow and evolve. We adapt today to win tomorrow.

What we offer:

• Medical insurance and financial aid;

• Benefit Cafeteria (compensation for the gym/stomatology/psychological service & etc.);

• 100 % paid sick leaves;

• Paid vacation;

• Annual salary review (based on performance);

• Quarter bonuses according to the company’s policy;

• Individual annual training budget which allows to visit paid conferences, training sessions, English lessons, workshops, etc.;

• Growe University (Leadership Programs, Knowledge sharing, Webinars, etc.);

• Personal development plan;

• Corporate events and team-building activities;

• Growe Care (Well-being Program);

• Free lunches at the office.

Growe welcomes those who are excited to:

• Define and drive the company-wide AI strategy, identifying key opportunities for AI transformation across products, engineering, and operations;

• Develop and maintain the AI adoption roadmap, including the selection of AI technologies, tools, and platforms;

• Integrate AI solutions into company processes, including software development, data analysis, QA/testing, documentation, and customer support workflows;

• Build and support internal platforms and tools that enable teams to effectively leverage AI capabilities;

• Collaborate with engineering, analytics, and product teams to identify and implement practical AI use cases;

• Lead internal AI initiatives, including experimentation, proof-of-concept projects, and rapid evaluation of emerging AI tools;

• Educate and support teams in adopting AI tools and best practices through workshops, training sessions, and internal knowledge sharing;

• Promote and develop a strong AI-driven culture across the organization;

• Provide internal AI consulting to business units, helping identify opportunities and evaluate the potential ROI of AI initiatives.

We need your professional experience:

• 8+ years of experience in technology companies, preferably in software engineering, platform engineering, or data/AI-related roles;

• Proven experience implementing new technologies and driving technical transformations at an organizational level;

• Hands-on experience working with modern AI technologies and ecosystems, including LLM-based tools and AI-powered workflows;

• Strong understanding of AI solution architecture and integration of AI tools into developer workflows;

• Experience leading process improvements or transformations in engineering teams;

• English - upper-intermediate or higher (able to communicate in technical discussions);

• Experience implementing AI coding assistants or AI tools for developer productivity (will be a plus);

• Experience working with AI agents or agent-based systems (will be a plus);

• Experience building internal developer platforms or engineering productivity tools (will be a plus);

• Experience working with data platforms or ML infrastructure (will be a plus).

We appreciate if you have those personal features:

• Strategic thinking and the ability to identify high-impact AI opportunities;

• Strong communication skills and the ability to explain complex technical concepts in a clear and accessible way;

• Ability to influence teams and drive change without direct managerial authority;

• Strong problem-solving and experimentation mindset;

• Curiosity and passion for emerging technologies and innovation;

• Ability to balance long-term strategy with fast experimentation and practical delivery.

We are seeking those who align with our core values:

• GROWE TOGETHER: Our team is our main asset. We work together and support each other to achieve our common goals;

• DRIVE RESULT OVER PROCESS: We set ambitious, clear, measurable goals in line with our strategy and driving Growe to success;

• BE READY FOR CHANGE: We see challenges as opportunities to grow and evolve. We adapt today to win tomorrow.

Role Overview:

We are looking for an Software Engineer, AI Systems to help build the backend architecture behind our emerging agent systems. This role sits at the intersection of software engineering, data infrastructure, and applied AI. You will work across the stack to design and implement systems that power LLM-driven product capabilities — from orchestration and tool integration to evaluation and production deployment. You’ll collaborate closely with product managers, designers, and engineers to bring AI-powered workflows directly into our underwriting platform. This is a high-impact role with significant ownership over both experimentation and production implementation. This role is ideal for engineers who enjoy working across layers of the stack and are excited about shaping how agent systems operate inside real production software.

What You'll Be Doing:

• Design and implement agent workflows and orchestration systems for AI-powered product features
• Build backend services that integrate LLMs with structured insurance data and platform APIs
• Develop infrastructure for tooling, context management, and agent execution
• Contribute to internal frameworks supporting prompt iteration, evaluation, and observability
• Partner with product and design to translate underwriting workflows into AI-enabled product experiences
• Help define architectural patterns for building reliable AI-native features in production
• Work across backend systems, data infrastructure, and product integrations to ship user-facing capabilities

Who We Hope You Are:

• 10+ years of experience in backend engineering, data engineering, or related roles
• Strong experience building production backend systems and APIs
• Professional experience working with LLMs, agent systems, or generative AI applications
• Hands-on experience with prompt design, tool-based agent architectures, or LLM workflows
• Proficiency in Python or similar backend languages
• Experience working with cloud infrastructure and distributed systems
• Comfort working across layers of the stack, from infrastructure to product integration
• Strong curiosity about emerging AI architectures and agent patterns
• Comfortable navigating ambiguity and working in a fast-paced, collaborative environment

Bonus Points if...

• Experience building production systems involving LLMs, agents, or prompt pipelines
• Experience designing internal platforms or developer tooling
• Familiarity with insurance, fintech, or B2B SaaS
• Contributions to open-source AI or data infrastructure projects
• Experience with Typescript

Why This Role Matters

You will help build the core infrastructure that powers the next generation of Federato’s platform. Your work will shape how AI systems interact with underwriting workflows and how intelligent automation is delivered to customers. This is an opportunity to work on foundational architecture for agent-driven software, with real-world impact in one of the world’s largest industries.

Base Salary: $215,000 - $250,000 a year
Final offer amounts are determined by multiple factors including candidate location, experience and expertise and may vary from the amounts listed above. Total compensation package includes stock options, benefits and additional perks. 

We are looking for a highly motivated and results-driven Head of Data to join our team full-time. In this strategic role, you will shape the vision, architecture, and delivery frameworks for Data Engineering, Data Science, Quant, and Data Analytics, unifying these teams into a single, high-impact function. This is a key leadership position, guiding both technical and managerial directions for our data organization.

We drive fintech innovation through deep analytical expertise and a data-first, engineering-driven approach.

Key Responsibilities

Data & Quant Leadership

• Define and lead the strategy across Data Engineering, Data Science, Quant, and Data Analytics, focusing on high business impact
• Build and manage cross-functional teams, including quants, data scientists, engineers, and analysts
• Drive advanced analytics, ML strategy, feature engineering, and model development with a focus on responsible AI
• Collaborate with stakeholders to turn complex business challenges into data-driven solutions

Data Engineering Leadership

• Design and evolve a scalable, reliable, and maintainable data platform architecture
• Oversee development of robust ETL/ELT pipelines and real-time data streams
• Establish engineering best practices: code reviews, CI/CD, data contracts, observability
• Drive technology selection and resource planning for ClickHouse, Spark, and supporting infrastructure
• Ensure data quality through monitoring, alerting, SLA ownership, and remediation processes

People & Cross-Functional Leadership

• Communicate effectively across technical and non-technical teams to influence decisions
• Lead cross-team processes (e.g., grooming, design reviews, retrospectives)
• Mentor team members, create growth plans, and foster a culture of psychological safety, accountability, and innovation

AI & LLM Strategy

• Define and drive GenAI and LLM strategy: identify high-value use cases, evaluate model providers (OpenAI, Anthropic, open-source), and lead end-to-end implementation
• Architect and oversee LLM-powered products: RAG pipelines, AI agents, and intelligent automation workflows integrated into core business processes
• Lead adoption of agentic AI frameworks (LangChain, LlamaIndex, AutoGen) to build autonomous multi-step reasoning systems
• Establish MLOps and LLMOps best practices: model versioning, evaluation frameworks, prompt management, and monitoring for drift and hallucinations
• Drive responsible AI governance: bias detection, explainability (SHAP, LIME), fairness auditing, and compliance with emerging AI regulations
• Champion AI-assisted development workflows (GitHub Copilot, Cursor) and foster an AI-augmented engineering culture across data teams
• Evaluate and integrate vector databases (Pinecone, Weaviate, pgvector) and embedding strategies to power semantic search and knowledge retrieval
• Collaborate with product and engineering to productionize AI features with robust feedback loops, A/B testing, and continuous model improvement

Requirements

• 7+ years of hands-on experience across Data Science, Quant, Data Engineering, delivering end-to-end solutions
• 3+ years of managerial experience, leading data teams including quants and data scientists
• Bachelor’s or Master’s degree in Computer Science, Mathematics, Physics, Engineering, or a related field
• Strong programming skills in Python, with experience writing clean, production-grade code
• Solid understanding of software engineering best practices (CI/CD, testing, code reviews, clean architecture)
• Practical experience with ML libraries and platforms (e.g., scikit-learn, XGBoost, PySpark)
• Deep understanding of core ML algorithms: regression, gradient boosting, time series, etc.
• Strong foundation in mathematical statistics, probability theory, and quantitative modeling
• Hands-on experience with LLMs, prompt engineering, and building production-grade AI systems (RAG, agents, fine-tuning)
• Familiarity with LLMOps tooling: experiment tracking (MLflow, W&B), vector stores, evaluation frameworks (RAGAS, DeepEval)
• Proficient in SQL and experience with analytical and OLAP databases
• English Upper-Intermediate

Nice to Have

• Experience with ClickHouse or other OLAP databases
• Background in trading or fintech
• Experience analyzing and modeling time series or high-frequency data
• Familiarity with anti-fraud systems, risk modeling, or portfolio analytics

We offer

• 20 paid vacation days per year
• 10 paid sick leave days per year
• Public holidays according to current legislation
• Medical insurance
• Opportunity to work remotely
• Professional education budget
• Language learning budget
• Wellness budget (gym membership, sports gear and related expenses)

eClinical Solutions is a global leader in clinical data intelligence, delivering the elluminate® Clinical Data Cloud® — an AI-powered platform driving agentic data review, SDTM automation, and RBQM for 18 of the top 50 pharmaceutical companies worldwide.

As part of our eNOVA AI-First transformation, we are embedding AI across every pillar of clinical development and enterprise operations — compressing cycle times, improving data quality, and redefining how work gets done.

As we scale our AI capabilities, we are building a high-impact, hands-on AI engineering function focused on delivering real, production-grade automation across the enterprise.

You will make an impact:

The Principal AI Engineer – Automation & AI is a hands-on technical leader responsible for designing, building, and deploying AI-powered automation solutions across eClinical Solutions.

This role is builder-first (70–80% hands-on development) and operates within a small, high-output team (2–4 engineers). You will work directly with the CTAO and business leaders to identify high-value use cases and rapidly translate them into working AI systems in production.

This is not a program management or oversight role. You are expected to build, ship, and iterate continuously, leveraging modern AI tooling and agentic frameworks to deliver measurable impact.

Accelerate your skills and career within a fast-growing company while impacting the future of healthcare.

Your day to day:

Building & Shipping AI Systems

• Design and deploy agentic AI workflows and automation solutions across enterprise functions including R&D, Engineering, Professional Services, IT, Finance, Sales, and Marketing
• Build production-grade systems such as:
• Multi-agent workflows
• RAG-based applications
• Document intelligence and summarization pipelines
• Workflow and process automation solutions
• Use modern AI tools and frameworks including:
• Codex, Claude Code, Gemini, NotebookLM
• LangChain, LangGraph, LlamaIndex (or equivalents)
• Rapidly prototype, validate, and deploy solutions in weeks, not months

Owning End-to-End Delivery

• Translate business problems into working AI systems
• Design lightweight architectures and iterate quickly
• Develop and implement:
• Prompt engineering strategies
• Orchestration logic
• API integrations and data pipelines
• Testing, validation, and monitoring frameworks
• Partner directly with stakeholders to refine outputs and drive adoption

Driving High-Velocity Execution

• Deliver continuous output with weekly or bi-weekly releases
• Prioritize use cases based on:
• ROI and business impact
• Technical feasibility
• Speed to value
• Operate with minimal process and high accountability in a fast-paced environment

Contributing to Scalable AI Foundations

• Build and maintain reusable assets including:
• Prompt templates
• Agent design patterns
• Integration utilities
• Contribute to lightweight standards for:
• Security and data handling
• Responsible AI practices
• Evaluation and performance monitoring

Technical Leadership & Mentorship

• Provide technical guidance to a small team of AI engineers and automation specialists
• Lead by example through hands-on contribution
• Support the evolution of the AI engineering function as it scales

Take the first step towards your dream career. Here is what we are looking for in this role.

Qualifications: 

• Bachelor’s degree in Computer Science, Engineering, Data Science, or a related technical field
• 6–10+ years of software engineering experience with recent hands-on work in AI/LLM systems
• Proven experience building and deploying:
• LLM-powered applications
• Agentic workflows
• Automation solutions in production environments
• Strong hands-on experience with tools such as:
• Codex, Claude Code, Gemini, NotebookLM (or similar AI-assisted development tools)
• LangChain, LangGraph, LlamaIndex, or equivalent frameworks
• Proficiency in:
• Python
• API development and system integration
• Cloud platforms (AWS, Azure, or GCP)

Preferred

• Experience with:
• RAG architectures and vector databases
• AI evaluation frameworks, guardrails, and monitoring
• Workflow automation tools and enterprise integrations
• Experience working in regulated environments (e.g., life sciences, healthcare, financial services)
• Familiarity with clinical data, CDISC standards, or clinical development workflows
• Experience in high-growth or PE-backed SaaS environments

Accelerate your skills and career within a fast-growing company while impacting the future of healthcare. We have shared our story, now we look forward to learning yours!

eClinical is a winner of the 2025 Top Workplaces USA Award for Remote Work! We have also received numerous Top Workplaces Culture Excellence Awards celebrating our exceptional company vision, values, and work-life balance. See all the details here: https://topworkplaces.com/company/eclinical-solutions/

eClinical Solutions is a people first organization. Our inclusive culture values the contribution that diversity brings to our business. We celebrate individual experiences that connect us and that inspire innovation in our community. Our team seeks out opportunities to learn, grow and continuously improve. Bring your authentic self, you are welcome here!

We are proud to be an equal opportunity employer that values diversity. Our management team is committed to the principle that employment decisions are based on qualifications, merit, culture fit and business need.

About the Role
We are seeking GTM Engineering interns to join our team for 6-12 months, with the opportunity to become a full-time team member afterwards pending performance. Interns will work closely with our GTM team on automating workflows and designing demos for client prospects. Interns will have an opportunity to work with cutting-edge AI technology and to be part of a dynamic and innovative team.

What you will be working on Weekly Basis

• Build and iterate on AI-powered go-to-market tools that help Safari AI scale outreach and accelerate deals
• Develop solutions that are robust across customer contexts: varying industries, use cases, and stages of the sales funnel, ensuring a consistent and compelling prospect experience
• Work with a growing team of sales, marketing, and product engineers to ship GTM experiments quickly and feed learnings back into the product roadmap
• Design and maintain the systems, templates, and data pipelines that power outbound sequences, lead nurturing flows, and customer onboarding
• Build and maintain AI-driven prospect research and account-scoring pipelines that surface high-fit venues (stadiums, theme parks, retail, cruise, ski) and enrich them with operational signals (camera count, footprint, parent org, tech stack)
• Develop vertical-specific demo environments and ROI calculators that translate Safari AI's computer vision outputs (queue times, dwell, occupancy, conversion) into language and metrics each buyer persona cares about
• Operate the outbound infrastructure stack — sending platform, CRM, enrichment, and reply-handling agents — and continuously tune deliverability, persona logic, and conversation state machines based on live performance data

Requirement for the Role

• Only students who can commit 6 months (2026/04-2027/01) will be screened
• Senior undergraduate or graduate school students in computer science or relevant field with exposure to classic and modern computer vision and machine learning techniques
• Excellent written and verbal communication skills
• Self-motivated, critical thinking and enthusiastic in solving real-world problems
• Experience with public cloud such as GCP, Azure or AWS
• Ability to design, implement, present, and operate independently without oversight
• Good business insight and exceptional analytical skills
• Comfortable wiring together modern GTM tooling (HubSpot, SmartLead/Instantly, Clay, Apollo, Zapier/n8n, Notion) and writing light Python or TypeScript to glue systems together
• Hands-on experience prompting and orchestrating LLM APIs (Anthropic, OpenAI) for production use cases — not just chat, but agents, classification, and structured output
• Working knowledge of SQL and at least one data warehouse or relational DB (PostgreSQL, BigQuery, Snowflake)

Nice to Have's

• Experiences in startup environment
• Exposure to B2B enterprise sales motions, especially with non-technical buyers in physical-venue industries (sports, hospitality, retail, attractions)
• Familiarity with computer vision concepts and the operational realities of CCTV/IP camera deployments
• Prior work building internal tools, dashboards, or AI agents that were actually adopted by a non-engineering team

What Safari AI Offers

• An opportunity to shape an early-stage AI startup and revolutionize how businesses get data and make decisions
• Professional growth at a fast-growing, venture-funded startup with a proven founder and leadership team

What you will do: 

Who we are:

At Focused, we move quickly to deliver quality software that achieves client outcomes and meets their customer’s needs. We strategically partner with our clients to leverage our expertise in design and software, while our clients bring their own domain expertise. We work with a variety of clients from different industries, collaborating as we get new products to market, modernizing legacy systems, or helping teams learn the skills they need to be successful.   

Our values:

• Listen first • We are experts in product practices but life long learners in the domain of our customers. We research, collaborate, and understand. 
• Learn why • We ask questions and talk to users to understand problem spaces, objectives, and goals, which allows us to deeply invest and drive towards the outcomes of our clients. 
• Love your craft • We love diving into a variety of domains and solving problems.  We take pride in delivering value, in communicating progress, and guiding our clients to success.

At Focused, our Engineers are both practitioners and experts in their craft. This role would play a crucial role in shaping and implementing engineering best practices and ensuring the successful delivery of complex software projects. With clients, we develop trust and influence - we are unintimidated and unintimidating. With colleagues, we set the standard for how we deliver success for clients.

What would you be doing?

• Directly engage with clients and provide expertise through pair programming and development on LangChain / LangGraph powered applications
• Deep expertise in LangChain, LangGraph and LangSmith
• Lead teams through end-to-end delivery across the stack, from backend services to modern web UIs.
• Pair program daily with teammates and clients to share knowledge, improve code quality, and grow together.
• Practice TDD and continuous refactoring to ensure code is reliable, maintainable, and understandable.
• Guide architecture decisions to support scalability, observability, and performance.
• Collaborate closely with designers, product managers, and stakeholders to continuously deliver valuable software.
• Coach developers on the team through pairing, mentoring, and modeling healthy engineering culture.
• Influence technical direction beyond the team, working across client orgs and Focused’s internal practices to share lessons, shape approaches, and raise the collective bar.
• Stay curious through experimenting with new patterns in the GenAI space, share what works (and what doesn’t), and help evolve how we build AI-powered software.

We are excited about you, because you:

• You’re a hands-on, full stack engineer with a strong track record of delivering software in collaborative, agile environments.
• You’ve worked with LangChain (or similar agentic frameworks), and understand how to architect AI-native systems responsibly and effectively.
• You have experience leading engineering teams and feel confident mentoring and supporting other developers.
• You believe that code quality matters, and that TDD and pairing help build better systems and stronger teams.
• You’ve worked across multiple languages or frameworks (e.g., Python, Node, Java, React, Next.js) and are pragmatic about tool selection.
• You’re excited about what’s happening in the AI space but stay focused on delivering value.
• You have experience navigating complex organizations, building bridges across functions, and helping teams adopt modern development practices.
• You’re as comfortable in the code as you are in a client meeting and can translate technical risks and wins into language anyone can understand.
• You love to share what you’re learning and make the team around you better.

If you had worked at Focused over the last 3 months you may have:

• Paired with a teammate to build a document Q&A system using LangChain and OpenAI APIs
• Helped design an architecture that integrates LLM agents into a legacy enterprise workflow
• Refactored a flaky test suite to support continuous delivery with confidence
• Mentored a junior dev through their first pairing and TDD session
• Built and deployed a full stack GenAI MVP with a React frontend and FastAPI backend
• Facilitated an architecture spike to evaluate vector database options for semantic search
• Contributed a new section to our internal AI playbook
• Helped write this job req

What to know before you apply: 

• This role will require working in a client office in the greater Dallas, TX area three days per week and up to 20% travel within the United States.
• Focused is unable to sponsor or take over sponsorship of the employment Visa process at this time.
• The Colorado base salary range for this role is $175,000 - $250,000.

About Arize AI

At Arize AI, we’re building the category-defining platform for AI observability, evaluation, and reliability.

AI is moving fast, but most teams are still flying blind once their agents hit production. We help teams understand how their agents behave, evaluate performance, and improve over time.

Our mission is simple: build the feedback loop that helps teams ship agents that actually work in the real world.

The Role

We’re looking for someone who thinks like a marketer and acts like a journalist to bring clarity to how modern AI systems are built and improved. This is a technical content role. You’ll work directly with engineers, researchers, and product teams to understand how AI systems actually work. Then, you’ll turn that into content that helps other engineers build, evaluate, and ship with confidence.

This role isn’t about summarizing ideas. It’s about extracting real workflows, pressure-testing them, and publishing content that’s immediately useful. You should already have a strong technical foundation. You’ll be expected to engage deeply with topics like evaluation, observability, agents, and LLM systems — and translate them without losing precision.

You’ll operate as both a strategist and a high-output individual contributor in a role where what you create ships quickly and gets used.

What You’ll Do

Write Technical Content That Engineers Actually Use

• Produce high-quality technical content: deep dives, guides, tutorials, and system-level explainers
• Break down complex topics (evals, agents, observability, prompt iteration) into clear, actionable workflows
• Focus on content that helps developers do something, not just understand something

Interview and Partner with Subject Matter Experts

• Work directly with engineers, researchers, and customers to extract insights and real-world workflows
• Ask strong technical questions and push for clarity where things are vague
• Turn conversations into structured, high-signal content

Define Content Strategy (and Execute It)

• Identify gaps in what developers are struggling with
• Prioritize and ship content that addresses those gaps
• Balance long-term narrative with immediate, high-impact output

Be an AI Native 

• Use AI tools to accelerate writing, editing, and research
• Build systems that increase content velocity without lowering quality
• Treat content as a compounding system, not a one-off deliverable

Work Cross Functionally

• Partner with Product, DevRel, and Marketing to ensure accuracy and relevance
• Align content with what’s actually shipping
• Contribute to how Arize explains AI engineering as a discipline

What We’re Looking For

Technical Background

You must be comfortable writing about: 

• Software engineering
• AI/LLM application development
• Developer workflows 

This is not a role for someone learning the space from the outside.

Content & Communication

• Strong writing and editing skills — you can explain complex systems clearly without oversimplifying
• Experience creating technical content (blogs, guides, docs, or similar)
• Ability to interview SMEs and turn conversations into structured, useful content 

Operator Mindset

• You can think strategically and execute tactically
• You ship consistently and take ownership of output
• You’re comfortable working in a fast-moving, high-ownership environment

AI-Native Workflow

• You actively use AI tools in your day-to-day work
• You think in terms of leverage, iteration, and systems
• You’re interested in how AI changes how content gets created

Nice to Have

• Experience building or working with LLM-based systems (RAG, agents, eval frameworks)
• Experience writing tutorials or developer documentation
• Background spanning both technical work and editorial/journalism

Why This Role Matters

AI systems are getting more complex, and harder to reason about.

The limiting factor for most teams isn’t access to models. It’s understanding:

• what to evaluate
• how systems fail
• how to improve them

Your job is to make that legible for engineers who are actively building.

Why Arize

• • Work at the center of the AI engineering ecosystem
  • Help define how AI systems are evaluated and improved
  • Build content that reaches and helps real practitioners
  • High ownership, fast iteration, and direct impact

Salary Range $160,000-$190,000 plus a generous equity package depending on experience

The Company

Outrider is a software company that is automating distribution yards with electric, self-driving trucks. Our system eliminates manual tasks that are hazardous and repetitive while it improves safety and efficiency. Outrider’s mission is to drive the rapid adoption of sustainable freight transportation. We are a private company founded in 2018 and backed by NEA, 8VC, Koch Disruptive Technologies, NVIDIA, and other top-tier investors. Our customers are Fortune 200 companies and our autonomous trucks are already running in distribution yards. For more information, visit www.outrider.ai

Overview

We are seeking a Data Engineer with strong Python and distributed processing skills to design, build, and maintain scalable data pipelines and the infrastructure behind our analytics products. This role focuses on delivering reliable, performant data systems by developing robust ETL/ELT workflows, optimizing data storage and processing, and ensuring data availability and quality at scale.

Key Responsibilities

• Design, build, and maintain scalable ETL/ELT pipelines that ingest, transform, and deliver data across the organization.
• Develop and optimize distributed data processing jobs using Python for large-scale data transformation and aggregation.
• Architect and manage PostgreSQL schemas, tables, indexes, and query performance to support downstream analytics and reporting.
• Build and maintain Python-based data workflows to orchestrate, validate, and deliver data reliably across environments.
• Monitor and improve data quality, freshness, and completeness through automated checks, alerting, and observability tooling.
• Design and manage cloud-based data infrastructure on AWS
• Partner with data analysts and stakeholders to translate requirements into well-modeled, maintainable data products.
• Maintain documentation for pipelines, data models, data lineage, and infrastructure.
• Troubleshoot pipeline failures and data issues, providing timely root-cause analysis and remediation.

Required Qualifications

• Experience: 3+ years of professional experience in data engineering.
• PostgreSQL: Schema design, indexing strategies, query optimization, and performance tuning.
• Python: Pipeline development, data validation, and orchestration frameworks.
• Distributed Processing and Storage: Hands-on production experience with tools such as AWS Athena, Apache Spark, etc.
• ETL/ELT: Proven experience designing and implementing pipelines in production.
• Cloud: AWS (S3, EKS, Glue, Athena).
• Data Modeling: Dimensional modeling, data warehousing patterns, and reproducible transformations.
• Engineering Practices: Git workflows, code reviews, testing, and CI/CD.
• LLM AI Agents: ability to use agents effectively to increase output.

Preferred Qualifications

• Experience with workflow orchestration tools (e.g., AWS Step Functions, Prefect, Dagster).
• Familiarity with modern data stack concepts: ELT patterns, data lakehouse architecture, semantic layers, and governance.
• Experience implementing automated data quality frameworks and pipeline observability.
• Exposure to streaming or near-real-time data processing (e.g., Kafka, Spark Streaming, Pub/Sub).

What Success Looks Like

• Reliable pipelines.  Pipelines are performant and trusted by downstream consumers.
• Maintainable infrastructure.  Data systems are well-documented, cost-efficient, and easy to extend.
• Proactive quality.  Data issues are detected early, with clear ownership and fast resolution paths.
• Consistent delivery.  Data is correctly modeled and delivered on time across all environments.

Skills & Attributes

• Systems-level thinking with strong attention to correctness, reliability, and scale.
• Ability to balance delivery speed with data quality, maintainability, and cost efficiency.
• Clear written and verbal communication with both technical and non-technical partners.
• Comfortable owning end-to-end data products from architecture through production support.

Assignment: 

• 4-month contract with possibilities to extend

Overview

The centralized Data and Analytics team at Recharge delivers critical analytic capabilities and insights for Recharge’s business and customers. 

As a Senior Data Engineer, you will build scalable data pipelines and infrastructure that power internal business analytics and customer-facing data products.  Your work will empower data analysts to derive deeper strategic insights from our data, and will  enable developers to build applications that surface data insights directly to our merchants. 

What you’ll do

• Build data pipeline, ELT and infrastructure solutions to power internal data analytics/science and external, customer-facing data products.
• Create automated monitoring, auditing and alerting processes that ensure data quality and consistency.
• Work with business and application/solution teams to implement data strategies, build data flows, and develop conceptual/logical/physical data models
• Design, develop, implement, and optimize existing ETL processes that merge data from disparate sources for consumption by data analysts, business owners, and customers
• Seek ways to continually improve the operations, monitoring and performance of the data warehouse
• Influence and communicate with all levels of stakeholders including analysts, developers, business users, and executives.
• Redesign and optimize existing data processes using AI (e.g., LLM-assisted development, automated documentation, issue resolution) to improve team productivity and enhance data quality across the data warehouse
• Live by and champion our values: #day-one, #ownership, #empathy, #humility.

What you’ll bring

• Typically, 5+ years experience in a data engineering related role (Data Engineer, Data Platform Engineer, Analytics Engineer etc) with a track record of building scalable data pipeline, transformation, and platform solutions. 
• 3+ years of hands-on experience designing and building data pipelines and models  to ingesting, transforming and delivery of large amounts of data, from multiple sources into a Dimensional (Star Schema) Data Warehouse, Data Lake.
• Experience with a variety of data warehouse, data lake and enterprise data management platforms (Snowflake {preferred}, Redshift, databricks, MySQL, Postgres, Oracle,  RDS, AWS, GCP)
• Experience building data pipelines, models and infrastructure powering external, customer-facing (in addition to internal business facing) analytics applications.
• Solid grasp to data warehousing methodologies like Kimball and Inmon
• Experience working with a variety of ETL tools. (FiveTran, dbt, Python etc)
• Experience with workflow orchestration management engines such as Airflow & Cloud Composer
• Hands on experience with Data Infra tools like Kubernetes, Docker
• Expert proficiency in SQL
• Strong Python proficiency

Interview recording & AI notetakers
To protect privacy, legal compliance, and interviewer/candidate experience, recording, transcribing, or using AI notetaker tools during interviews is not permitted without our prior written consent. Handwritten notes are welcome. If you need an accommodation (e.g., captions), email recruiting@getrecharge.com before your interview—we’ll arrange an approved solution.

Compensation 

Recharge’s compensation offerings are grounded in a pay-for-performance philosophy that recognizes exceptional individual and team performance. Salary ranges are designed to be competitive and aligned with country specific practices, while individual compensation is determined by skills, qualifications, and experience. The compensation listed is not inclusive of any equity and benefits that might exist in your total compensation package.

• Hiring range in the US
  $148,000 USD - $185,000 USD
• Hiring range in Canada
  $108,000 CAD - $136,000 CAD

Application window anticipated to close: 6/1/2025. If you’re interested in this opportunity, please submit an application as soon as possible.

Team: Revenue Operations
Reports to: Chief Revenue Officer
Location: Remote
Type: Full-time

The Role

You'll be Product Owner across three surfaces:

• CRM — platform, data model, permissions, lifecycle automation.
• Partner Product — the cabinet, dashboards, payout logic, and tooling our IBs, affiliates, and KOLs live in.
• Marketing Enablement — lifecycle stack, AI agents, and the internal tools BD/AM run on.

You own the roadmap, backlog, specs, and outcomes with a simple goal in view - to grow revenue.

We want a disruptor. Someone who sees a 14-step nurture sequence and asks why an agent isn't running it. Someone comfortable in a product review with engineers and a funnel economics conversation with the CEO.

What You'll Do 🛠

CRM

• Lead the new CRM rollout and adoption across BD, Partnerships, AM, Marketing, Compliance, Support.
• Own the data model, permissions, and the pipe from platform → warehouse → CRM → activation.

Partner Product

• Own the IB/affiliate/KOL product experience end-to-end.
• Translate partner and BD feedback into a prioritised backlog; ship with engineering.
• Build the partner journeys, onboarding, activation, tiering, qualification that turn signups into revenue.

Revenue org Enablement & AI

• Ship AI auto-funnels: agents that score, personalise, route, draft, and hand off.
• Embed AI into daily BD/AM work: prospect intelligence, meeting prep, auto-logged notes, next-best-action, call QA.
• Support Acquisition and Retention teams with setting up funnels across email, in-app, SMS, push.

Always

• Test, measure, kill what doesn't work.
• Report ROI clearly. Iterate.

What We're Looking For 🪄

Must-haves

• Product ownership experience with a track record.
• Experience in CRM integration/management (Salesforce, HubSpot, Zoho, Zendesk, Customer.io, Braze, or similar).
• Experience in shipping funnels that actually convert.
• Hands-on with AI in a revenue context: LLM APIs, agents, prompt engineering, AI-powered outbound.
• Strong with Dev, Data, Marketing, Sales. Translates well between them.
• Analytical. Reads cohorts and retention curves, not just reports.

Bonus points for

• Owning a partner/IB/affiliate product before.
• Shipped AI agents on top of a CRM (scoring, outreach, research, QA).
• Tools: n8n, Make, Zapier Agents, Clay, Apollo, Smartlead, HeyReach, Retell, Bland.
• Fintech, crypto, brokerage, iGaming, or other regulated, affiliate-heavy verticals.
• RAG, vector DBs, internal knowledge agents.
• A portfolio that shows what you've built, not just where you've worked.

About the role:

We’re looking for a Senior Machine Learning Engineer to accelerate our AI research-to-production pipeline. You’ll build and improve the infrastructure that enables our research team to rapidly deploy and safely test new models, while helping ensure our production inference systems remain efficient, scalable, and reliable. You’ll identify gaps and opportunities in our ML infrastructure, scope solutions to ambiguous technical problems, and help set the technical direction for how we bridge research innovation and production reliability. This role requires a strong backend engineering background in distributed systems and containerization, and a track record of independently driving projects from concept to delivery. This is a cross-functional role that requires close collaboration with both research teams developing models and engineering teams supporting the broader platform.

What You’ll Do:

• Design and implement tooling that enables researchers to quickly deploy and evaluate new models in production 
• Design, build, and maintain high-performance, cost-efficient inference pipelines, making architectural decisions about scaling, reliability, and cost trade-offs
• Proactively identify and resolve infrastructure bottlenecks, proposing and scoping improvements to iteration speed and production reliability
• Develop and maintain user-facing APIs that interact with our ML systems
• Implement comprehensive observability solutions to monitor model performance and system health
• Troubleshoot and lead resolution of complex production issues across distributed systems, driving root-cause analysis and implementing preventive measures
• Set the direction for and continuously improve our MLOps practices, identifying the highest-impact opportunities to reduce friction between research and production.
• Collaborate closely with research and engineering teams to align on technical direction, and help onboard and mentor engineers on ML infrastructure best practices.

What You’ll Need:

• Strong backend engineering experience with Python
• Experience building and operating distributed, containerized applications, preferably on AWS 
• Proficiency implementing observability solutions (monitoring, logging, alerting, tracing) for production systems
• Ability to design and implement resilient, scalable architectures
• Track record of independently scoping and delivering complex technical projects from problem identification through production deployment
• Comfort navigating ambiguity and making pragmatic technical decisions when requirements are unclear or evolving

An ideal candidate should also have some of the following:

• MLOps experience, including familiarity with PyTorch and Kubernetes
• Experience working in fast-paced environments where you owned technical direction for an area and drove projects with minimal oversight.
• Experience collaborating with remote, globally distributed teams
• Comfort working across the entire ML lifecycle from model serving to API development
• Experience in audio-related domains (ASR, TTS, or other domains involving audio processing)
• Experience with other cloud providers
• Familiarity with Bazel and monorepos
• Experience with alternative ML inference frameworks beyond PyTorch
• Experience with other programming languages
• Experience mentoring junior engineers or onboarding teammates onto complex systems

Pay Transparency:

AssemblyAI strives to recruit and retain exceptional talent from diverse backgrounds while ensuring pay equity for our team. Our salary ranges are based on paying competitively for our size, stage, and industry, and are one part of many compensation, benefit, and other reward opportunities we provide.

There are many factors that go into salary determinations, including relevant experience, skill level, qualifications assessed during the interview process, and maintaining internal equity with peers on the team. The range shared below is a general expectation for the function as posted, but we are also open to considering candidates who may be more or less experienced than outlined in the job description. In this case, we will communicate any updates in the expected salary range.

The provided range is the expected salary for candidates in the U.S. Outside of those regions, there may be a change in the range which will be communicated to candidates throughout the interview process.

Salary range: $195,000 - $225,000

Remote | Full-time

Born in the Basque Country and built for the world, ZenRows is one of the fastest-growing data infrastructure startups in Europe. We work 100% remotely and hire the best people regardless of where they are.

Founded in 2021, we started as a scraping API for developers. In 2026, we are evolving into something bigger: the data collection infrastructure layer for the AI era. Thousands of companies across e-commerce, finance, real estate, and AI rely on ZenRows to power their data pipelines. Now, we're building for the next generation of users: workflow builders, AI engineers, and business teams who don't write code but need data to flow reliably through their systems.

We're looking for a Head of Content to own how ZenRows is discovered, understood, and trusted across LLMs, developer communities, integration ecosystems, and the open web.

The Role

This is not a content volume role. It's a content positioning role.

The way developers and technical teams discover tools has fundamentally changed. Google search is no longer the only, or even the primary surface. Developers ask ChatGPT. Business users ask Gemini. AI engineers search Perplexity. Workflows are built inside Clay, n8n, and Make, where discovery happens through directories, templates, and community recommendations.

Your job is to make ZenRows the trusted, cited, recommended answer across all of these surfaces, not just in Google's top 10.

You'll work closely with Product, Sales, and the GTM Engineer to ensure content is a genuine growth engine, not a support function.

What You'll Own

🔍 AEO, GEO & Discoverability Strategy

This is the core of the role.

• Own ZenRows' Answer Engine Optimization (AEO) and Generative Engine Optimization (GEO) strategy: ensuring we are the cited, recommended answer when developers and AI engineers ask about web scraping, data collection, workflow automation, and data pipelines
• Understand how LLMs (ChatGPT, Gemini, Claude, Perplexity) surface and prioritize content, and build a strategy around it
• Develop structured, citation-friendly content formats: comparison pages, definitional guides, integration explainers, and technical FAQs that earn LLM citations
• Own competitive intelligence: track how competitors are being cited, recommended, and positioned in AI search

📊 SEO Strategy & Content Operations

• Own ZenRows' organic search strategy end-to-end: keyword research, topic prioritization, content gap analysis, and competitive benchmarking, with a clear view of where SEO still drives meaningful pipeline and where it doesn't
• Lead content operations: manage the editorial calendar, maintain publishing velocity, and ensure quality standards across in-house writers, freelancers, and external agencies
• Manage, and develop a team of technical writers and editors, setting clear briefs, review processes, and feedback loops that raise the floor on content quality without creating bottlenecks
• Own the relationship with external content agencies: briefing, quality control, performance review, and deciding what stays in-house versus what gets outsourced
• Develop and maintain off-page SEO strategy: link acquisition, guest publishing, and building the kind of third-party authority signals that reinforce ZenRows' position in both traditional search and LLM training corpora
• Work closely with Engineering on technical SEO: site architecture, crawlability, Core Web Vitals, structured data markup, and indexing health, you won't do this alone, but you'll own the roadmap and hold the team accountable
• Maintain a content performance framework: define and track the metrics that matter (organic traffic, keyword rankings, assisted conversions, LLM citation frequency) and use them to make prioritization decisions, not just report on them
• Continuously audit the existing content library for decay, cannibalization, and coverage gaps, and make the hard calls about what gets updated, consolidated, or cut

🧑‍💻 Developer Education & Docs-as-Marketing

• Turn ZenRows' documentation into a top-of-funnel acquisition channel. Think Stripe's docs: content that ranks, educates, and converts, not marketing fluff disguised as technical writing
• Build actionable, developer-focused resources: integration tutorials, use-case walkthroughs, SDK examples, and migration guides
• Create content specifically for the AI/LLM data pipeline audience: tutorials on using ZenRows for RAG pipelines, AI agents, training data collection, MCP server integrations, and agentic workflows
• Collaborate with Engineering and Product to ensure documentation is accurate and genuinely useful
• Partner with DevRel to amplify technical content across developer communities

🔗 Ecosystem & Integration Content

This is new territory for ZenRows, and one of the highest-leverage content surfaces in 2026.

• Build and maintain a library of integration content: how ZenRows works inside Clay, n8n, Make, Zapier, LangChain, LlamaIndex, and other workflow and AI platforms
• Create content that earns ZenRows a presence in integration marketplaces and community directories, not just Google
• Partner with the Partnerships Manager on co-marketing content: joint guides, partner-specific tutorials, template libraries
• Develop content that serves workflow builders and automation teams: non-developer technical users building workflows and automation without writing code

📈 PLG Content & Activation

• Build a content-led activation flywheel: blog post attracts developer → documentation helps them succeed → integration guide shows them what's possible → usage converts to paid
• Partner with Product and Growth on in-app content, onboarding flows, and activation-focused tutorials
• Own the content layer of the trial-to-paid conversion journey

🤝 Sales Enablement & Enterprise Content

• Support Sales with high-impact materials: competitive battle cards, use-case one-pagers, ROI narratives, and case studies
• Develop positioning content for workflow builders and automation teams, as well as business users who interact with data through AI tools and LLM interfaces
• Build and maintain a lean, current library of sales enablement assets, prioritize quality and relevance over volume

👥 Team Leadership

• Lead, mentor, and develop the existing content team
• Define and maintain editorial standards and brand voice across all content types
• Build a culture of experimentation and outcome orientation, not content volume
• Scale through leverage: AI-assisted workflows, freelance network, and smart prioritization

The Person

We're looking for someone who thinks in distribution systems, not publishing calendars.

Required

• 5+ years in content, growth, or developer marketing, ideally at a B2B SaaS, API, or developer infrastructure company
• Deep understanding of AEO and GEO: you know how LLMs source and surface answers, and you've thought about what it means for content strategy
• Technical fluency in developer tools, APIs, or adjacent infrastructure. You don't need to be an engineer, but you need to be able to write or edit a Python snippet, understand what a headless browser does, and explain a web scraping use case to a non-technical audience
• Proven experience building content for both self-serve/PLG and integration-led or enterprise motions
• Strong editorial judgment, you can tell the difference between content that educates and content that fills a calendar
• Experience building and maintaining integration or ecosystem content: tutorials, partner guides, marketplace presence
• Comfortable operating in a fast-moving, autonomous environment without heavy process
• Fluent in English (we are an English-first organization)

Strong Advantage

• Experience with workflow automation platforms (Clay, n8n, Make, Zapier) from a content or product perspective
• Familiarity with the LLM/AI agent ecosystem: LangChain, LlamaIndex, CrewAI, RAG architectures
• Experience evolving or rebuilding a content function through a GTM pivot, not just building from scratch
• Track record of content that drove ecosystem or community-led growth, not only organic search traffic
• Experience using AI-assisted tools to automate content operations at scale (n8n, Claude Code, or similar)

This Role Is Not For Everyone

• We are a small, efficient team of ~20 competing against companies 10x our size. Ownership is real, there is nowhere to hide
• We are fully remote, which means documentation and async communication are essential
• Feedback is constant and candid. Strong opinions are welcomed and debated
• We are scaling fast. Processes evolve. Priorities shift. If you need rigid structure, you may struggle
• We just made a significant strategic pivot. Some things that worked before won't work the same way. You'll need to be comfortable with that ambiguity

Why You'll Love Working Here

• You will own the entire content function at a critical inflection point, the work you do in 2026 will shape the company's market position for years
• Genuine autonomy. You will be trusted, not micromanaged
• Direct access to leadership, our CEO is accessible and values world-class talent
• 100% remote, forever
• A horizontal culture where contributing beyond your job description is expected and celebrated
• You'll be working at the intersection of developer tools, workflow automation, and the AI agent ecosystem, one of the most interesting spaces in tech right now

What Rewards and Benefits Would I Get?

• 100% remote work: true location freedom
• The salary you are worth: we focus on value, not previous compensation
• The equipment you want: choose the tools you need
• Generous Learning & Development budget: courses, materials, growth support
• BitWarden Account for secure password management
• Annual Kick-Off: yearly team event in a new location
• Barcelona Meetups throughout the year
• Deel Benefits: discounts on services, subscriptions, travel, and more
• Access to world-class colleagues reinventing an industry

Our Values

Ownership, Dedication, Impact, Transparency, and Agility run through everything we do. We're a sociable company and don't let a remote model stop us from feeling connected. The atmosphere is friendly, supportive, and driven by a constant desire to improve.

Diversity, Equity & Inclusion

At ZenRows, we are committed to diversity, equity, and inclusion and recognize we can always do more. Every job description is reviewed through a gender bias decoder to ensure inclusivity. We aim to nurture a welcoming and safe environment for everyone.

Privacy and Your Data

At ZenRows, we prioritize the privacy and security of data entrusted to us. We comply with all applicable data protection regulations and industry best practices. Any job offer will be subject to successfully passing background checks.

At Mammoth Growth, the Senior Analytics Engineer / Jr. Tech Lead focuses on building complex data infrastructure using dbt, Snowflake, and modern ELT tools while providing technical guidance and expertise. You'll design scalable data pipelines, implement governance frameworks, and leverage AI tools to optimize development workflows. The position requires hands-on technical work combined with code review responsibilities and team guidance.

What You'll Do

• Build complex data models using dbt with optimal performance and maintainability 
• Design and optimize Snowflake data pipelines leveraging advanced features for scalability
• Configure database environments, manage permissions, access control, and implement data governance frameworks
• Implement ELT processes using modern data stack tools such as Fivetran
• Write high-quality code following Git workflows, code reviews, and CI/CD practices
• Conduct data quality audits and implement automated testing frameworks
• Leverage AI tools (Claude, ChatGPT) to enhance development productivity and solution quality
• Apply prompt engineering and implement agentic workflows using MCPs
• Mentor Analytics Engineers I and II, providing technical guidance and code reviews 
• Collaborate with Technical Leads and Sr. Consultants on complex project decomposition and execution 
• Present technical solutions and audit findings to clients
• Independently manage project components while coordinating with cross-functional teams
• Support project planning with technical expertise and risk assessment

What You'll Bring

Technical Skills

• Advanced dbt proficiency with complex modeling, macros, and performance optimization
• Deep Snowflake expertise including architecture, optimization, and advanced features
• Hands-on experience with Fivetran and modern data stack ecosystem 
• Proficient in Git/GitHub workflows, branching strategies, and collaborative development
• Advanced SQL skills with query optimization and performance troubleshooting 
• Understanding of dimensional modeling and analytics engineering methodologies
• Experience with cloud environments and scalable solutions in AWS and/or GCP
• Familiarity with project management tools like Jira

AI & Innovation Skills

• Demonstrated experience with Claude, ChatGPT, and other LLM platforms
• Familiarity with agentic tools such as CoPilot, RooCode, and others
• Prompt engineering skills for code generation, documentation, and problem-solving
• Strong interest or direct experience in agentic workflows and Model Context Protocols (MCP)
• Ability to integrate AI tools into technical workflows

Professional Skills

• 5-7+ years of analytics engineering or data engineering experience
• Strong problem-solving abilities with complex technical challenges
• Excellent communication skills for technical and business stakeholders
• Experience mentoring junior team members
• Self-motivated with ability to work independently and collaboratively

Who We Are (Mode Mobile)

Mode Mobile is the creator of EarnOS, a transformational software that turns ordinary smartphones into "EarnPhones." This innovation empowers users globally to monetize everyday mobile activities such as streaming, gaming, shopping, etc. We enable users to profit from their data and attention rather than letting only tech giants benefit. Our inclusive approach sets us apart - converting users into earners and facilitating over $150M in earnings and savings while going a step further and turning earners into owners by awarding stock ownership in Mobile Mobile based on their usage. We have attracted over 40 million users across 170 countries.  

​​Mode Mobile is proud to stand as the #1 Fastest-Growing North American Software Company recognized in Deloitte's 2023 Technology Fast 500 and ranked #2 across all sectors.

For additional insights, check out the information about our reward-based super app, Mode Earn App, which also powers the reward engine behind our proprietary smartphone, Mode Earn Phone.

Our Team and Culture Drive Our Success

Our team is the heart of our culture.  We value innovation, collaboration, and curiosity, with a passion for getting things done.  We strive to hire and cultivate the best team members and foster a culture of open communication and transparency.  We are driven and hard-working but also committed to having fun along the way.  We allow OKRs to guide us, assume positive intent, sometimes agree to disagree and commit, honor our commitments, seek to accomplish more with less, and encourage everyone to speak up as our team owns our company’s success.

You can read more about our team and how we work here.

The Opportunity

The new Market Research business unit will be focused on data monetization, market intelligence, and research-driven revenue. The General Manager of Mode Market Research will build this business from the ground up, own multiple revenue streams, and turn underutilized data assets into meaningful profit centers. We are looking for a founder-minded General Manager to build this business from zero to recurring, enterprise-grade revenue.

The GM of Mode Market Research will own four data monetization segments and one existing web product. The mission is to create revenue lines, structure partnerships, collaborate with the Chief Data Officer and product teams, and scale each business into an independent profit engine with dedicated staff. The first phase is hands-on execution. Hiring follows once revenue baselines are met. This role blends data strategy, partnerships, product execution, and full P&L responsibility.

This is not a traditional management role. This is a revenue-building, hands-on operator role with full ownership.

AI & Data Innovation Ownership

• Design and implement AI-driven data products, including predictive models, LLM-powered insights, and automated reporting tools
• Leverage modern AI stacks (e.g., LLMs, embeddings, vector databases) to transform raw datasets into scalable intelligence products
• Identify opportunities to replace manual workflows with agentic AI systems that accelerate revenue generation
• Partner with the Chief Data Officer to integrate AI capabilities into Mode’s data infrastructure and EarnOS ecosystem

What You’ll Own

Audience and Profile Data Monetization

Build Mode’s audience and profile data business by defining datasets, structuring a centralized data lake, and partnering with major marketplaces.

• Monetize email lists, user profiles, and audience data across Mode’s product portfolio
• Partner closely with the Chief Data Officer to structure scalable data pipelines
• Establish and manage partnerships with data marketplaces and identity platforms (e.g., LiveRamp, Experian, and similar platforms)
• Build revenue before adding dedicated sales support

Receipt Scanning and Commerce Intelligence

Turn existing receipt-scanning and Trimbox shopping data into institutional-grade purchase intelligence.

• Standardize purchase and transaction data across Mode product lines
• Collaborate with the Chief Data Officer and product teams to ensure data quality, consistency, and usability
• Establish direct sales relationships and channels with hedge funds and research buyers

App Usage, Installed App Graph, and Web Behavior

Scale Mode’s market-data business by selling insights directly to enterprise buyers.

• Expand Mode’s app usage and behavioral intelligence offerings beyond SDK-based monetization 
• Co-own the vertical in partnership with the GM of Mode Earn App
• Work with the Chief Data Officer to improve data completeness, coverage, and reliability

Location Data Monetization

Rebuild Mode’s geo-data revenue line and expand it with new high-value partners.

• Identify up to three profitable location-data partners
• Work with the product org on integration
• Co-own this vertical with the GM of Earn App

Who You Are

You are a founder-style builder who:

• Has built or scaled 6-7 figure ARR in data, SaaS, or analytics businesses
• Has sold directly to enterprise or institutional buyers
• Thinks in terms of margin and lifetime value
• Is comfortable operating without a large team
• Moves quickly and eliminates ambiguity
• Understands privacy frameworks and data governance standards

You are as comfortable closing a contract as you are defining the product.

Success Profile

The ideal candidate collaborates closely with product, data, business development, and revenue. You’ll execute quickly, eliminate ambiguity, and build repeatable revenue lines from assets that already exist within the business. You are comfortable starting as an operator and evolving into a leader who hires and manages a small team.

Why Join Mode Mobile

• Be part of a company where the culture is the magic. Our team consistently says the best part of Mode is the people - collaborative, humble, hungry, and genuinely invested in each other’s success.
• Make an impact on millions of users across a global social platform with massive scale and cultural relevance.
• Work with a global, top-tier engineering team that cares deeply about craftsmanship, velocity, and helping each other win.
• Shape the next stage of a high-growth social platform, entering an exciting next phase of growth, scale, and innovation.
• Join a mission-driven culture where ownership is real, ideas travel fast, and your work has a visible impact.
• Grow inside a fast-growing, post-acquisition business backed by strong leadership and investment in monetization, UA, and product innovation.
• Work fully remote with a globally distributed team that values autonomy, trust, and transparent collaboration.

Alignment with Our Core Values:

• ​​Accountable: You take ownership of your responsibilities, demonstrating trustworthiness and self-discipline. You are consistent in your work, transparent in your actions, and communicate effectively. You follow through on commitments and strive for continuous improvement.
• Action-driven: Identify what is most important, agree on scope, execute in a timely manner, and drive the greatest impact.  You take initiative, roll up your sleeves, and get things done.
• Caring: You genuinely care about yourself and others, our business and craft, our mission and vision, and are passionate in heart and mind. You understand the importance of our team and strive to create a positive, supportive work environment.
• Curious: You focus on the ‘why,’ learn and expand your knowledge, explore new ideas, and generally make things better.  You're a lifelong learner with a thirst for knowledge and a constant desire to improve.
• Thorough: Your work is thoughtful, impactful, timely, accurate, and complete.  You pay attention to detail, are meticulous, and ensure quality work and compliance.

We Believe in the Following Workplace Norms

• Allow OKRs to Guide Us
• Assume Positive Intent
• Agree to Disagree & Commit
• Set New Precedents
• Accomplish More with Less
• Hold Yourself & Others to High Standards
• Speak Up
• Be Resourceful
• Follow the 80/20 Rule

What We Are Offering

• We are a 100% remote-first, global company.
• A competitive compensation package.
• We offer generous perks & benefits to team members. 
• Participation in the Company's equity plan (for full-time team members).
• We provide individual bonuses in accordance with our Company Bonus Program.
• Work with energetic, passionate, and results-driven people.
• Celebrate team members' personal and work milestones.
• Remote social activities, including virtual coffee buddies. 
• Bonusly - We use Bonusly as a way to recognize and reward team members for their hard work and commitment.
• Weekly Wednesday Get Stuff Done Days (No Meetings).
• Open PTO, generous Company Holidays, and Wellness Days (for full-time team members).

If we just described you and your perfect role, we'd love to talk with you.  We have a lot to accomplish this year and look forward to making headway and creating success together!

Mode Mobile does not accept/pay fees for unsolicited resumes from third-party agencies/vendors.

Our company is an Equal Employment Opportunity (EEO) employer. We are committed to providing a work environment free of discrimination and harassment. All employment decisions are made without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other characteristic protected by law. We celebrate diversity and strive to create an inclusive environment for all team members.

Meet the team:

The Developer Platform team as a part of Software Foundations and Architecture is responsible for building and maintaining the infrastructure that enables all developers to track, build, deploy and operate our software.  From the build system everyone uses, to the tools used to submit and deploy changes, to the cloud infrastructure they use to operate it - we support the entire development experience.  The Developer Platform team forges the tools that empower the entire software engineering organization while working with engineers from almost every team.

Roles & Responsibilities:

• Act as the primary Product Owner for the Continuous Integration (CI) system, managing how it centrally runs builds and tests by seamlessly hooking into source control, the build system, and integrating tightly with Buildkite and GitHub
• Design and implement short and long term scalable integrations that connect Bazel with the CI/CD pipelines to automate workflows, integrate with AI/LLM/Agent tools, trigger specific jobs, manage build artifacts, and ensure proper handoffs
• Build, scale, and manage the CI AWS infrastructure, overseeing capacity planning and actively working to optimize performance by reducing job execution times
• Develop comprehensive observability (including logs, metrics, traces, and alerts) into the CI infrastructure to accurately track system efficiency, identify errors, and focus reliability efforts.
• Maintain the CI system as a reliable, high-performing platform, providing day-to-day on-call support, incident management, and troubleshooting for the wider software engineering organization.

Knowledge, Skills and Abilities:

• Strong knowledge of CI/CD best practices and principles. Direct experience with Buildkite is a plus.
• Experience working with infrastructure as code technologies such as Terraform or equivalent.
• Experience observability technologies like Promtheus, OpenTelemetry or similar.
• Experience with Linux operating systems in both day to day development and operational environments.
• Strong knowledge of AWS or other similar cloud platforms.
• Bonus would be knowledge building services and tools in Go, Python or similar languages.

About Sharebite

Sharebite is the leading meal benefits platform built exclusively for companies to feed their employees. Our platform allows employees to order meals from any restaurant while streamlining all of the ordering & billing requirements for the company. Every meal ordered through the Sharebite platform results in a meal donation to local partners like City Harvest and Feeding America to help combat food insecurity. To date, Sharebite has donated over 15 million meals.

About the Role

As an AI Engineer, you will play a key role in shaping how Sharebite applies AI across both its product and internal operations. You will begin by working closely with the product and engineering teams to build a deep understanding of the codebase, core workflows, business logic, and operational complexity behind the platform. We see that foundation as essential to building AI solutions that are not only innovative but genuinely useful.

As you grow into the role, you will identify high-impact opportunities to use AI to improve efficiency, streamline manual work, and enhance the product experience for customers and internal teams. You will be responsible for designing, building, and refining AI-powered tools, automations, workflows, and product features that are practical, scalable, and well-integrated into the business. This role is ideal for someone who wants to pair full stack engineering with applied AI work and have a meaningful influence on how the function develops over time.

A note on the role: this position starts as a Full-Stack Engineer and evolves into an AI Engineer over time. If you’re looking for a pure AI/ML research role, this likely is not the best fit. If you’re someone who loves building real products and wants to apply AI engineering over time, this role is perfect for you.

What You’ll Do

• Build and ship full-stack features across the product as you ramp up on the platform
• Develop a thorough understanding of our systems, data models, and business logic
• Identify high-leverage automation opportunities as you learn how the platform works
• Design and build AI agents and automated workflows using modern AI tooling
• Integrate LLMs into product workflows in ways that are reliable and production-safe
• Evaluate, iterate, and improve AI systems based on real-world performance
• Collaborate with product and engineering to solve user-facing problems
• Help define what effective, responsible AI engineering looks like at our company

Required Skills & Experience

• 5+ years of full-stack development experience, with a proven ability to own features end-to-end
• 1–2 years of hands-on AI engineering experience building and shipping LLM-powered systems in production
• Experience with at least one major AI orchestration framework such as LangChain, LangGraph, or AWS Bedrock
• Familiarity with LLM APIs (OpenAI, Anthropic, etc.), vector databases, RAG pipelines, and agent frameworks
• Strong software engineering fundamentals, including system design, testing, debugging, and clean code practices
• Clear communicator who can work across product and engineering teams

Who You Are

• Genuinely curious about how systems work, and not just how to layer AI on top of them
• Comfortable starting as a full-stack engineer and growing into AI engineering as you learn the product
• Thoughtful about where AI adds real value and where it doesn’t
• Someone who takes ownership and doesn’t wait to be told what to improve
• Excited by the idea of being the person who shapes how an entire company thinks about AI

What Success Looks Like

• 0–3 months: You’re shipping product features independently and have a strong mental model of how the platform works
• 3–6 months: You’ve shipped your first AI-powered workflow or agent into production
• 6–12 months: You’ve automated multiple high-impact workflows and are proactively identifying the next wave of opportunities

At Sharebite, we are committed to providing competitive pay in line with industry and market standards. The base compensation range for this role is $110-$130k per year, however actual compensation packages are based on a wide array of factors unique to each candidate including but not limited to skill set, years & depth of experience, and location. Salary is just one component of Sharebite's total compensation package, which includes equity, multiple health insurance options, and a wide range of benefits, including a daily meal stipend.

Bioinformatics Machine Learning Intern

RefinedScience | United States (hybrid or remote)

At RefinedScience, our mission is to advance care by bringing together the best science, data and minds – disease by disease, patient by patient, cell by cell to discover pathways to life beyond disease.

What We Are Looking For

We are seeking a highly motivated Bioinformatics Machine Learning Intern to join our team. This internship is designed for Ph.D. candidates with experience applying machine learning, deep learning, or generative AI methods to single-cell omics data. You will contribute to active projects spanning single-cell biology, multiomics integration, and computational approaches to precision medicine and drug development.

Our Bioinformatics team plays a crucial role in integrating computational biology, large-scale data analysis, and machine learning to drive discoveries in precision medicine and drug development.

Key Activities

• Analyze single-cell and multiomics datasets to extract biological insights supporting precision medicine and drug development programs
• Apply and evaluate machine learning and deep learning approaches to single-cell data for tasks such as cell type classification, biomarker discovery, and patient stratification
• Explore and prototype generative AI and LLM-based approaches to accelerate biological data interpretation and scientific workflows
• Collaborate with scientists, clinicians, and data scientists to design and execute data-driven research projects
• Document and optimize computational workflows following reproducible research best practices
• Present findings through technical reports, visualizations, and presentations to cross-functional teams

Must Haves

• Current Ph.D. candidate in Bioinformatics, Computational Biology, Computer Science, Biostatistics, or a related quantitative field
• Single-cell omics experience: Demonstrated ability to process, analyze, and interpret single-cell data (scRNA-seq, scATAC-seq, CITE-seq, or spatial transcriptomics) using frameworks such as Scanpy/scverse, Seurat, or Bioconductor
• Machine learning expertise: Applied experience developing and evaluating ML/deep learning models on biological data, including neural network architectures (GNNs, transformers, autoencoders), model selection and benchmarking, and integration of ML approaches into analytical workflows
• Programming proficiency: Python and/or R for data analysis, statistical modeling, and visualization
• Statistical foundation: Understanding of statistical methods for biological data (hypothesis testing, differential expression, multiple testing correction, clustering)
• Strong problem-solving skills and ability to communicate complex insights effectively

Desired Qualifications

Machine Learning & AI

• Experience with deep learning frameworks (PyTorch, TensorFlow, JAX)
• Familiarity with graph neural networks, attention mechanisms, or transformer architectures applied to biological data
• Experience with ML experiment tracking and reproducibility (MLflow, Weights & Biases)
• Exposure to representation learning, variational autoencoders, or contrastive learning methods
• Familiarity with scikit-learn, XGBoost, or similar ML libraries
• Interest in or experience with LLMs, RAG systems, or agentic AI tooling

Bioinformatics

• Experience with multimodal single-cell integration (Seurat WNN, scvi-tools/MultiVI/totalVI, Muon)
• Familiarity with spatial transcriptomics analysis (Squidpy, cell2location, nf-core/spatialvi)
• Experience with cell-cell communication inference (CellChat, NicheNet, LIANA)

• Knowledge of drug-gene interaction resources (CMap/LINCS, OpenTargets, ChEMBL)

Engineering & Infrastructure

• Familiarity with Linux/Unix CLI and version control (Git/GitHub)
• Experience with containerization (Docker, Singularity) and environment management (conda, venv)
• Exposure to cloud computing platforms (GCP preferred)
• Familiarity with workflow managers (Nextflow, Snakemake)
• Adherence to best-practices for conduct reproducible computational research

Duration

8–10 weeks

Why You'll Love RefinedScience

Team + Values

At RefinedScience, we seamlessly integrate top-tier clinical and biological data with expert knowledge to provide unparalleled insights. We maximize patient impact with these unique insights by optimizing clinical trial probability of success and time to actionable results. We work across biopharma and we are a trusted partner in achieving better results, faster – working together to unlock strategic advantage.

Our Values

• Act with Purpose – We believe in rigor through deliberate and thoughtful actions
• Be Curious – Curiosity is the spark that ignites innovation and growth
• Take Ownership – True ownership leads to pride and commitment in the work we do
• Invest in Relationships – Building strong connections is the foundation for effective collaboration and trust for long term success
• Embrace Agility – We celebrate agile thinking, resilience, and adaptability

Compensation

• $34-$38 per hour

Compensation: $80,000 - $100,000 OTE

Location: Remote

About Martell Group

The Martell Group exists to build people, brands, and ventures that create meaningful impact. Across our four companies, we combine audience, operators, and execution to launch scalable products and empower ambitious leaders in Media, B2B SaaS, and AI.

Founded by serial entrepreneur and investor Dan Martell (investor in Udemy, Intercom, and Unbounce), we’re building a company that values leadership, growth, and simplicity, and we’re looking for people who live those values too.

Our goal is to attract world-class talent and align people where their impact is greatest. When you apply to Martell Group, you’ll automatically be considered for all open roles across our companies, not just the one you applied for.

Why you shouldn't work here – Radical Transparency from our CEO

About the Role

You’ll be Engineer #5, a core builder of one of our umbrella companies, the AI-powered CFO designed to solve operational finance for founders. Our platform replaces manual spreadsheets and lagging accounting data with real-time visibility, intelligent bookkeeping, and proactive financial controlling. You will be responsible for moving the product through our 3-phase roadmap: from real-time data aggregation to AI-driven automated collections and payments.

What you'll do

• Data Ingestion & Normalization: Plug into bank feeds (Plaid), accounting software (QuickBooks/Xero), and payment processors (Stripe/Shopify).
• AI-Powered Categorization: Deploy agents to analyze, classify, and map transaction data to specific clients, product lines, and regions.
• Conversational Intelligence: Enable founders to query their financial data using natural language (LLM-driven intent detection).
• Real-Time Projections: Calculate cash burn, runway, and margin analysis using live data streams.
• Automated AR/AP Engine: Build proactive monitoring systems that trigger automated reminders, escalating collections, and pre-approved payment workflows.

• Design and Implement Scalable Services: Build robust backend logic for financial data processing using TypeScript and Node.js.
• Integrate 3rd Party APIs: Deeply integrate with Stripe, Shopify, QuickBooks, Xero, and banking APIs to ensure seamless data flow.
• Build AI Workflows: Implement agentic frameworks (Google Agent SDK, Vercel AI SDK) for automated bookkeeping and debt collection.
• Optimize Financial Logic: Develop and refine algorithms for cash flow forecasting, margin analysis, and profitability mapping.
• Full-Stack Ownership: Work across frontend and specialized backend microservices to ship user-facing features quickly.
• Troubleshoot & Refactor: Pick up existing code, identify bottlenecks, and refactor for efficiency and abstraction.

Tech Stack

• Frontend: Vue, TypeScript
• Serverless Backend: Convex
• AI/LLMs: Gemini, Claude, OpenAI
• Agent Frameworks: Google Agent SDK, Vercel AI SDK, Maestra, Convex
• Database: Convex
• Integrations: Stripe, Shopify, QuickBooks, Xero, Square, Plaid
• Architecture: Separated concern environments, Microservices

• 5+ years of experience as a Full-stack or Backend-heavy Engineer.
• You’ve built and worked on end-to-end saas, AI, fintech platforms convering all areas of the system
• AI-First Mindset: You live the 10/80/10 principle (10% paper/brainstorming, 80% AI generation, 10% human refinement).
• Problem Solver: You don’t just write code; you solve hard problems with creative human input.
• Fast Shipper: You thrive on seeing your code in production quickly and aren’t precious about “perfection” over “progress.”
• Team Player: You understand the impact of others relying on you and value proactive communication/syncing.
• Detail-Oriented: You think ahead about the impact of small mistakes in financial data environments.

• Finance/Accounting Background: Prior experience with ERPs, bookkeeping systems, or fintech startups.
• Big Data Experience: Experience handling large-scale transaction data and microservices architecture.
• UI/UX Design: An eye for clean, functional design for financial dashboards.

Compensation: $80,000 - $100,000 OTE

Location: Remote

About Martell Group

The Martell Group exists to build people, brands, and ventures that create meaningful impact. Across our four companies, we combine audience, operators, and execution to launch scalable products and empower ambitious leaders in Media, B2B SaaS, and AI.

Founded by serial entrepreneur and investor Dan Martell (investor in Udemy, Intercom, and Unbounce), we’re building a company that values leadership, growth, and simplicity, and we’re looking for people who live those values too.

Our goal is to attract world-class talent and align people where their impact is greatest. When you apply to Martell Group, you’ll automatically be considered for all open roles across our companies, not just the one you applied for.

Why you shouldn't work here – Radical Transparency from our CEO

About the Role

You’ll be Engineer #5, a core builder of one of our umbrella companies, the AI-powered CFO designed to solve operational finance for founders. Our platform replaces manual spreadsheets and lagging accounting data with real-time visibility, intelligent bookkeeping, and proactive financial controlling. You will be responsible for moving the product through our 3-phase roadmap: from real-time data aggregation to AI-driven automated collections and payments.

What you'll do

• Data Ingestion & Normalization: Plug into bank feeds (Plaid), accounting software (QuickBooks/Xero), and payment processors (Stripe/Shopify).
• AI-Powered Categorization: Deploy agents to analyze, classify, and map transaction data to specific clients, product lines, and regions.
• Conversational Intelligence: Enable founders to query their financial data using natural language (LLM-driven intent detection).
• Real-Time Projections: Calculate cash burn, runway, and margin analysis using live data streams.
• Automated AR/AP Engine: Build proactive monitoring systems that trigger automated reminders, escalating collections, and pre-approved payment workflows.

• Design and Implement Scalable Services: Build robust backend logic for financial data processing using TypeScript and Node.js.
• Integrate 3rd Party APIs: Deeply integrate with Stripe, Shopify, QuickBooks, Xero, and banking APIs to ensure seamless data flow.
• Build AI Workflows: Implement agentic frameworks (Google Agent SDK, Vercel AI SDK) for automated bookkeeping and debt collection.
• Optimize Financial Logic: Develop and refine algorithms for cash flow forecasting, margin analysis, and profitability mapping.
• Full-Stack Ownership: Work across frontend and specialized backend microservices to ship user-facing features quickly.
• Troubleshoot & Refactor: Pick up existing code, identify bottlenecks, and refactor for efficiency and abstraction.

Tech Stack

• Frontend: Vue, TypeScript
• Serverless Backend: Convex
• AI/LLMs: Gemini, Claude, OpenAI
• Agent Frameworks: Google Agent SDK, Vercel AI SDK, Maestra, Convex
• Database: Convex
• Integrations: Stripe, Shopify, QuickBooks, Xero, Square, Plaid
• Architecture: Separated concern environments, Microservices

• 5+ years of experience as a Full-stack or Backend-heavy Engineer.
• You’ve built and worked on end-to-end saas, AI, fintech platforms convering all areas of the system
• AI-First Mindset: You live the 10/80/10 principle (10% paper/brainstorming, 80% AI generation, 10% human refinement).
• Problem Solver: You don’t just write code; you solve hard problems with creative human input.
• Fast Shipper: You thrive on seeing your code in production quickly and aren’t precious about “perfection” over “progress.”
• Team Player: You understand the impact of others relying on you and value proactive communication/syncing.
• Detail-Oriented: You think ahead about the impact of small mistakes in financial data environments.

• Finance/Accounting Background: Prior experience with ERPs, bookkeeping systems, or fintech startups.
• Big Data Experience: Experience handling large-scale transaction data and microservices architecture.
• UI/UX Design: An eye for clean, functional design for financial dashboards.

Principal AI Solutions Consultant

Our client is a healthcare organization specializing in Patient Support Programs, looking for a Principal AI Solutions Consultant to join their team on a contract basis. This is a practical, results-driven role focused on developing AI-powered automations and MVP solutions that streamline operations and enhance program visibility.

In this role, the Consultant will partner with Project Managers, Operations, and Clinical teams to turn real operational challenges into effective, user-friendly tools built on Microsoft 365, Power Platform, and large language models. Note that compliance, pharmacovigilance, DPIA, and patient data handling fall outside the scope of this role — those responsibilities sit entirely with the client's internal teams.

What You'll Be Doing

The Consultant will own the end-to-end delivery of focused, high-value MVPs and automations across 2–3-week sprints, with structured demos and knowledge transfer at each cycle. The engagement will span across 6-8 weeks, and full-time work may be available after this period. Work will span:

• Building a Trust Engagement Database leveraging tools such as Notion, SharePoint, or equivalent platforms.
• Developing Power Automate workflows and Copilot Agent assets — covering prompt libraries, lightweight agent frameworks, automated SLA reminders, email and Teams-based triggers, tracking dashboards, and recurring or on-demand reporting.
• Prototyping LLM-assisted Adverse Event (AE) triage workflows (non-PHI), encompassing classification and summarization logic, intelligent routing, and retrieval from approved content sources.
• Wrapping up solutions as reusable, well-documented components: data models, deployment runbooks, and step-by-step how-to guides.
• Working hand-in-hand with Project Managers and Operations to make sure every solution lands well and can scale.
• Contributing to the client's AI-driven Digital Transformation initiatives.

What We're Looking For

• Proven track record delivering production-ready automations within the Microsoft 365 ecosystem (SharePoint, Teams, Power Automate, Power BI).
• Hands-on experience working with LLM-based tools, prompts, or agent frameworks (Azure OpenAI, Copilot, Claude, or similar).
• Strong command of data modeling using Notion, Excel, CSV, and Microsoft Graph.
• History of shipping MVPs on tight, sprint-based timelines.
• Comfortable working in a contract/consultancy capacity. You must be available for 6 to 8 weeks of work, with the potential of staying on as a full-time staff member afterward.
• Background in pharma or healthcare — particularly familiarity with industry terminology — is a significant plus.

Nice to Have

• Experience integrating HubSpot or Microsoft Graph into existing workflows.
• Knowledge of evaluation frameworks for classification and summarization tasks.
• A portfolio of reusable internal tooling built for external clients.

Working Style & Values

• Able to navigate non-PHI environments confidently and responsibly.
• Highly organized with a sharp ability to prioritize under pressure.
• Thrives in dynamic, fast-moving settings.

Our client is a values-driven organization in the healthcare space, guided by the principles of caring, candor, and high performance. They are seeking someone who welcomes feedback, adapts their approach based on team input, and brings both conviction and humility to collaborative problem-solving.

if this sounds right for you, use the form below to apply!

Are you an AI QA expert eager to shape the future of AI? Large-scale language models are evolving from clever chatbots into enterprise-grade platforms. With rigorous evaluation data, tomorrow’s AI can democratize world-class education, keep pace with cutting-edge research, and streamline workflows for teams everywhere. That quality begins with you—we need your expertise to harden model reasoning and reliability.

We’re looking for AI QA trainers who live and breathe model evaluation, LLM safety, prompt robustness, data quality assurance, multilingual and domain-specific testing, grounding verification, and compliance/readiness checks. You’ll challenge advanced language models on tasks like hallucination detection, factual consistency, prompt-injection and jailbreak resistance, bias/fairness audits, chain-of-reasoning reliability, tool-use correctness, retrieval-augmentation fidelity, and end-to-end workflow validation—documenting every failure mode so we can raise the bar.

On a typical day, you will converse with the model on real-world scenarios and evaluation prompts, verify factual accuracy and logical soundness, design and run test plans and regression suites, build clear rubrics and pass/fail criteria, capture reproducible error traces with root-cause hypotheses, and suggest improvements to prompt engineering, guardrails, and evaluation metrics (e.g., precision/recall, faithfulness, toxicity, and latency SLOs). You’ll also partner on adversarial red-teaming, automation (Python/SQL), and dashboarding to track quality deltas over time.

A bachelor’s, master’s, or PhD in computer science, data science, computational linguistics, statistics, or a related field is ideal; shipped QA for ML/AI systems, safety/red-team experience, test automation frameworks (e.g., PyTest), and hands-on work with LLM eval tooling (e.g., OpenAI Evals, RAG evaluators, W&B) signal fit. Skills that stand out include: evaluation rubric design, adversarial testing/red-teaming, regression testing at scale, bias/fairness auditing, grounding verification, prompt and system-prompt engineering, test automation (Python/SQL), and high-signal bug reporting. Clear, metacognitive communication—“showing your work”—is essential.

Ready to turn your QA expertise into the quality backbone for tomorrow’s AI? Apply today and start teaching the model that will teach the world.

We offer a pay range of $6-to- $65 per hour, with the exact rate determined after evaluating your experience, expertise, and geographic location. Final offer amounts may vary from the pay range listed above. As a contractor you’ll supply a secure computer and high-speed internet; company-sponsored benefits such as health insurance and PTO do not apply.

Employment type: Contract
Workplace type: Remote
Seniority level: Mid-Senior Level

The Mission

We are a Delaware-incorporated, remote-first serial acquirer of SaaS companies across North America and Europe. With a portfolio spanning 6+ jurisdictions, a $100M debt facility, and a 400-person global team, our complexity is high, but our team is lean.

We are looking for our first General Counsel & Head of Legal Ops. We don't want to build a massive legal department; we want to build a massive legal advantage. You will be the architect of an AI-augmented legal and tax function that enables us to acquire 5+ companies per year with unprecedented speed and structural efficiency.

The "AI-First" Mandate

In this role, your "Junior Associate" and "Tax Senior" are Large Language Models (LLMs). You will:

• Scale through Automation: Implement AI-driven due diligence to audit hundreds of SaaS contracts in hours.
• AI-Augmented Tax Structuring: Use advanced AI agents to perform "first-pass" research on cross-border tax treaties (US/EU), transfer pricing logic, and permanent establishment risks.
• Self-Serve Governance: Deploy internal AI tools to handle 80% of routine queries from our global team regarding SARs, HR compliance, and NDAs.
• Outside Counsel Optimization: Act as a "sophisticated buyer" of legal and tax services—using AI to verify work and ensuring we only pay for high-level "human-in-the-loop" sign-offs.

Key Responsibilities

• M&A Execution: Lead the legal lifecycle of ~5 acquisitions/year. Own the SPA, manage local counsel in Europe/NA, and drive deals to close.
• Strategic Tax Structuring: Work at the intersection of legal and finance. Use AI to model tax-efficient deal structures (Asset vs. Share) and maintain our global transfer pricing framework between Delaware and our European subsidiaries.
• Debt & Capital: Manage our $100M debt facility—handling drawdowns, ensuring covenant compliance, and managing lender relations.
• Global People Ops: Oversee compliance for a 400-person workforce (FTEs, Contractors, EOR) across Germany, Austria, France, Finland, Canada, and the US.
• Equity (SARs): Manage and scale our Stock Appreciation Rights program globally.

Who You Are

• The M&A Quarterback: You have 6–10 years of experience (JD/LLM required), likely coming from a top-tier Private Equity or M&A practice.
• AI-Native: You don't just "use" AI; you prompt-engineer your workflow. You are comfortable building a "no-code" legal stack.
• The "Tax-Literate" Generalist: You aren't a CPA, but you understand the "geometry" of international tax. You can use AI to navigate a tax treaty and know exactly when to pull in a specialist for a final "stress test."
• Operational Mindset: You value deal velocity over long memos. You quantify risk in dollars, not just "could/might" language.

The Tech Stack You’ll Build

We expect you to own the budget for and implement:

1. AI Due Diligence: For contract analysis and liability mapping.
2. Entity Management: For our 6+ global subsidiaries.
3. CLM (Contract Lifecycle Management): To automate SaaS sales and vendor agreements.
4. Tax AI Research: To stay ahead of OECD/Pillar Two and local European tax changes.

Why Join Us?

• Blueprint Power: You are the first hire. You define the tech stack and the strategy.
• No Billable Hours: Success is measured by the efficiency of the "Acquisition Engine."
• High Leverage: Manage a $100M facility and a global portfolio with the best tools available.
• Incentives: Significant participation in our SAR program.

What’s in it for You

• Ultimate flexibility: We’re 100% remote. You can work from wherever you like, whenever you like.
• Freedom and autonomy: We’re a high-trust team, and you’ll be given lots of flexibility to solve problems in your own way — with plenty of help from the team when you need it.
• Minimum bureaucracy: We don’t like to get bogged down with meetings and red tape. We like to be efficient and keep momentum steady & sustainable.
• Small & friendly team: We help each other out, have fun, and joke around.
• Our network: We are a community of entrepreneurial SaaS professionals that regularly exchange ideas, knowledge, learning  and expertise with each other internally. 
• Flexible time off: We want you to recharge your batteries when needed.

We don’t just simply offer you to “take a job with us” but rather to “join us on this journey” to build the world's largest platform of independent SaaS companies. 

This role is part of our Central Team at saas.group.

What is saas.group?

We are a Delaware-incorporated, remote-first serial acquirer of SaaS companies across North America and Europe. With a portfolio spanning 6+ jurisdictions, a $100M debt facility, and a 400-person global team, our complexity is high, but our team is lean.

Profile Overview

As our first legal hire, you will build the legal function from the ground up, ideally super-lean by leveraging software, AI, and automation to maximize efficiency—minimizing the need for additional headcount or external counsel. We are a fast-moving serial acquirer of SaaS companies with a global team and a significant debt facility. You will be a key partner to the executive team, ensuring our acquisition engine runs smoothly, our global compliance is airtight, and our corporate governance supports our long-term growth.

Your immediate impact in the first 3-6 months will be:

• Establish a scalable, AI-driven legal operations framework to minimize reliance on external counsel.
• Audit and streamline the legal due diligence process for our M&A pipeline to support ~5 acquisitions per year.
• Take full ownership of the corporate secretarial duties and governance for our Delaware parent and global subsidiaries.

Your responsibilities

• M&A Execution: Lead legal due diligence and partner with the M&A team and the board during transaction execution; manage outside counsel across various jurisdictions to ensure deals are closed on time and within budget.
• Corporate Governance: Manage our Delaware parent entity and subsidiaries in Germany, Austria, France, Finland, Canada, and the US, acting as the corporate secretary for board meetings.
• Capital Structure & Debt: Oversee the legal requirements of our $100M debt facility, including compliance with financial covenants and reporting obligations.
• Global Employment & HR: Partner with People Ops to manage a hybrid workforce of 400+ (FTEs, Contractors, and EORs) and ensure our SAR (Stock Appreciation Rights) program is compliant.
• Commercial & SaaS: Streamline customer contracts and privacy policies (GDPR/CCPA) across the portfolio to ensure best-in-class standards.
• Risk & Compliance: Build scalable processes for IP protection, data privacy, and internal audits.

What You bring to the table

• Legal Qualification: JD, LLM, or equivalent degree, admitted to practice in a major jurisdiction (US or EU preferred).
• M&A & Private Equity Expertise: 6+ years of experience with a heavy emphasis on M&A or Venture Capital; in-house experience at a "buy-and-build" platform is a major plus.
• Cross-Border Proficiency: Comfortable navigating both US and European legal frameworks in a remote-first, asynchronous environment.
• Operational & AI Mindset: You view legal as a business enabler and are eager to adopt AI tools (like ChatGPT Enterprise or Gemini) to scale efficiency.
• Strategic Influence: Ability to set functional strategy, align with senior leadership, and act as a multiplier across the organization.

What's in it for You

• Ultimate flexibility: We're 100% remote. You can work from wherever you like, whenever you like.
• Freedom and autonomy: We're a high-trust team, and you'll be given lots of flexibility to solve problems in your own way.
• Minimum bureaucracy: We don't like to get bogged down with meetings and red tape. We like to be efficient and keep momentum steady & sustainable.
• Our network: We are a community of entrepreneurial SaaS professionals that regularly exchange ideas, knowledge, and expertise.
• Flexible time off: We want you to recharge your batteries when needed.

We don't just simply offer you to "take a job with us" but rather to "join us on this journey" to build the world's largest platform of independent SaaS companies.

Location: Remote

Duration: 2–4 months (project-based)

Type: Contract / Research Collaboration (Paid)

About the Project

We are looking for a Master’s or PhD student to work on fine-tuning large language models (LLMs) for domain-specific tasks. The goal is to take an existing pretrained model (e.g., Meta AI’s LLaMA-class models or similar) and specialize it for a narrow, high-value use case using efficient fine-tuning techniques.

This is a hands-on applied project designed for someone who wants real-world experience deploying and optimising LLM systems.

Help drive the next wave of applied AI by demonstrating how fine-tuned LLMs can unlock advanced, real-world use cases beyond general-purpose foundation models. Organizations that require domain-specific accuracy, self-hosted deployments, customisable workflows, or performance beyond out-of-the-box capabilities increasingly rely on fine-tuned models to meet those needs.

Through this project, you will contribute to building specialised AI systems that deliver improved accuracy, efficiency, and control compared to out-of-the-box models. You will also help bridge the gap between academic knowledge and real-world application by applying fine-tuning techniques to solve concrete business problems.

What You’ll Work On

• Fine-tuning pre-trained LLMs on small to medium datasets (500–20k examples)
• Implementing parameter-efficient fine-tuning (e.g., LoRA-style methods)
• Optimising training for cost and performance
• Running experiments on GPU cloud infrastructure
• Evaluating model performance and tradeoffs (specialisation vs generalisation)
• Deploying fine-tuned models for inference

Experience

• Strong Python skills
• Experience with deep learning frameworks: PyTorch (preferred) or TensorFlow
• Experience with Hugging Face Transformers or similar ecosystems
• Hands-on experience training or fine-tuning transformer models on GPUs (local or cloud-based)
• Previous experience using cloud platforms for model training or deployment (e.g., AWS, GCP, Azure, RunPod or similar GPU providers)
• Experience working with or fine-tuning open-weight LLM families (Gemma-3, Qwen-3.5, Llama 4, GPT-OSS, Mistral...)
• Hands-on experience with LoRA

Understanding of:

• Fine-tuning vs pretraining
• Overfitting and generalization
• Model evaluation
• Strong business awareness: ability to understand the context of the fine-tuning task and translate domain requirements into clear modeling objectives

What you bring

• MSc or PhD student in Computer Science, Machine Learning, AI, or related field
• Alternatively, 6 months of hands-on experience training and fine-tuning deep learning models
• Has worked on LLMs in research or industry
• Has fine-tuned at least one transformer model
• Comfortable working independently
• Interested in applied AI and real-world constraints (cost, latency, memory)

What You’ll Gain

• Real-world experience fine-tuning large models (30B–100B parameter class)
• Exposure to production constraints and deployment
• Opportunity to co-author technical writeups if applicable
• Strong applied portfolio project

What We Offer

• 100% Remote Work: Work from anywhere with flexibility and autonomy 
• Dynamic, High-Impact Projects: Work on cutting-edge ML and GenAI solutions across diverse industries
• International Clients: Collaborate with global organizations and solve real-world challenges at scale
• Urban Sports Club Membership: Supporting your physical and mental wellbeing
• Monthly Bolt Credits: For rides
• Company Events & Offsites: Regular team gatherings to connect, collaborate, and celebrate

Kotlin Expert (SME) – Consultant Description

Purpose

We are seeking a highly experienced Kotlin Software Engineering professional to serve as a Subject Matter Expert (SME) on advanced software development and AI benchmarking projects. This role is pivotal in designing, documenting, and validating Kotlin-based tasks and functionalities that test and refine the coding capabilities of large language models (LLMs) — particularly within Android development environments.

Your work will define both the technical standard and the functional scaffolding of real-world coding benchmarks, ensuring all tasks meet the highest levels of authenticity, precision, and reproducibility. You will help assemble datasets and functional frameworks that mirror the complexity and reasoning required in professional Android engineering.

Core Components

1. Functional Design, Documentation & Benchmark Definition

• Define, document, and validate Kotlin-based Android functionalities used in AI benchmarking and software simulation projects.
  • Author comprehensive functional and technical documentation, including feature requirements, system behavior, and expected outcomes.
  • Translate open-ended requirements into realistic, well-scoped Android tasks representing genuine engineering challenges.
  • Ensure each benchmark task is complete, verifiable, and grounded in authentic developer workflows.
  • Maintain structured repositories of Kotlin challenges, categorized by complexity, topic, and functional type.

2. Technical Standard Setting, QA & Process Improvement

• Define Kotlin-specific quality metrics, benchmarking criteria, and rubrics aligned with Android production standards.
  • Develop SOPs and QA frameworks enforcing stylistic consistency, idiomatic Kotlin use, and functional clarity.
  • Conduct rigorous QA passes on deliverables — verifying code correctness, documentation completeness, and benchmark adherence.
  • Apply quality principles to maintain dataset and code task evaluation standards.
  • Curate gold-standard Kotlin examples representing benchmark-worthy implementations.

3. Talent Definition, Vetting & Calibration

• Collaborate with recruitment and project leads to define role competencies for Kotlin contributors.
  • Develop technical evaluation frameworks for vetting Kotlin developers, including practical code tasks and debugging exercises.
  • Lead calibration sessions with contractors to ensure consistency and quality.
  • Create skill matrices and capability documentation for Kotlin engineering talent aligned to benchmarking needs.
  • Provide continuous feedback and training materials for quality improvement.

4. Benchmark Dataset Development & Validation

• Collaborate with AI research teams to design and refine Android benchmarking datasets for evaluating LLM coding performance.
  • Source, assess, and refine Kotlin-based Android tasks testing comprehension, reasoning, and problem-solving.
  • Document evaluation criteria including accuracy, code structure, and maintainability.
  • Contribute to post-project analysis, surfacing insights on performance trends and task design improvements.
  • Recommend dataset refinements to enhance domain coverage.

5. Project Delivery & Stakeholder Support

• Support project setup, scoping, and execution of Kotlin-oriented AI training and evaluation projects.
  • Provide expert-level input on tooling, frameworks, and pipeline design (Ktor, Jetpack, Gradle, KSP).
  • Collaborate closely with ML engineers, QA specialists, and data annotators to meet research-grade standards.
  • Produce summary documentation and retrospective reports detailing lessons learned and recommendations.

Target Profile

• 5+ years of professional experience in Kotlin software engineering (Android, backend, or multiplatform).
  • Mastery of Kotlin idioms, coroutines, Flow, Jetpack Compose, and asynchronous programming.
  • Experience in technical documentation, benchmark dataset design, or QA of coding tasks preferred.
  • Proven ability to define and enforce technical and stylistic standards across distributed teams.
  • Strong collaboration and communication skills with the ability to articulate complex logic clearly.
  • Exceptional attention to detail and documentation discipline.
  • Fluent in English, with precise writing and communication abilities.

Example Documentation & Benchmark Task Scope

Summary

This Kotlin SME role merges engineering excellence, documentation rigor, and benchmark development expertise. You will help shape the foundation for evaluating AI models in real-world Android engineering, defining how Kotlin is used to measure and guide the next generation of intelligent software systems.

We offer a pay range of $25-to- $65 per hour, with the exact rate determined after evaluating your experience, expertise, and geographic location. Final offer amounts may vary from the pay range listed above. As a contractor you’ll supply a secure computer and high‑speed internet; company‑sponsored benefits such as health insurance and PTO do not apply.

Job title: Kotlin Expert (SME)
Employment type: Contract
Workplace type: Remote
Seniority level: Senior Level

We’re hiring a VP of Product Management to lead and scale our Product Management organization for our AI-powered, Enterprise GRC platform. This role reports to the Chief Product Officer and serves as their primary partner in building an empowered product organization.

You’ll co-create the product strategy with the CPO and own the translation of that strategy into clear roadmaps, empowered teams, and consistent execution across the portfolio. You’ll manage and grow a team of PMs, evaluate and upgrade the existing org where needed, drive cross-functional alignment with Engineering and GTM, and act as a key product leader with customers, partners, and the board.

How you’ll spend your time: 

Lead and Scale the Product Management Organization

• Build, manage, and develop a high-performing PM team. Hire, onboard, and retain high performers. Be a talent magnet people want to work for.
• Continuously raise the bar for the PM organization through thoughtful hiring, coaching, role design, and career pathing, ensuring we have the right people in the right roles for our next stage of growth.
• Develop deep expertise in our platform, with a clear view of what we do well, where we need to grow, and an intuition for level of effort to support prioritization and escalation decisions.

Partner on Product Strategy & Own Execution

• Partner with the CPO to refine and evolve the product vision and multi-year strategy.
• Own the translation of strategy into a coherent portfolio roadmap, aligned with company goals.
• Ensure each product team has clear outcomes, priorities, and success metrics, and consistently challenge teams to tie their work back to company strategy and business impact.

Lead the Execution of our AI-Powered GRC Strategy

• Empower and upskill PMs to own AI features within their domains: establishing simple frameworks for identifying AI opportunities, evaluating feasibility, and designing safe, trustworthy AI experiences.
• Ensure AI features are grounded in real customer problems and workflows, not AI for AI’s sake.
• Collaborate with Security and Legal on risk, privacy, and governance for AI capabilities to create trustworthy experiences for our customers.

Own Product Operating Rhythms & Processes

• Own the product operating system: planning cadences, quarterly roadmapping, OKRs, and portfolio review.
• Ensure strong feedback loops from customers, GTM teams, and the market into product decision-making.
• Continuously refine processes to support scale while staying fast and agile.

Champion Empowered Product Teams

• Partner with Engineering and Design leaders to ensure teams are empowered, accountable, and outcome-focused.
• Embed discovery, prototyping, and experimentation into how product teams operate.
• Coach PMs on customer interviews, problem framing, hypothesis testing, and validation.

Drive Cross-Functional Alignment & Reduce Friction

• Work closely with Sales, Marketing, Customer Success, and Implementations to ensure roadmap and GTM alignment.
• Identify and clean up cross-functional misalignment and points of organizational collision.
• Stay calm, direct, and constructive during escalations, conflicts, and high-stakes situations.

Strong with Customers, Partners, and the Board

• Serve as a key product leader with customers: CAB, key accounts, strategic deals, and escalations.
• Represent the product roadmap and strategy with partners and at industry events when needed.
• Build credibility with internal and external stakeholders through clarity, honesty, and follow-through.
• Inspire and energize PMs and cross-functional partners about where we’re going and why, so teams feel more focused and motivated after interactions with you.

We get excited about you if you have:

• 15+ years in Product Management, with significant experience in B2B SaaS platform companies (multi-product, integrations, workflows, data).
• 3–5+ years directly managing PM teams, including scaling from small teams to 10+ PMs.
• Strong history of cross-functional leadership and resolving misalignment between Product, Engineering, and GTM.
• A track record of balancing strategic altitude with hands-on engagement – willing to dive into squads’ work when the stakes are high, while still empowering PMs to own their domains.
• Excellent communicator and storyteller: adept at framing product strategy and decisions for execs, customers, and boards.
• Calm, direct, and constructive during escalations, conflicts, and high-stakes situations and willing to dive into the details.
• Known by former PMs and peers as a motivating, present leader who makes time for coaching, career development, and honest feedback.
• Experience shipping LLM powered features and/or agents in production B2B SaaS products (e.g., recommendations, copilots, automations, or predictive insights).
• Experience leading Product Management in B2B SaaS companies in the $20M–$100M+ ARR range, ideally having helped scale a business 2–3x at that stage.
• Experience in GRC is a plus but not required. Success in complex B2B platform environments is an essential with proven ability to ramp quickly in complex domains.

Hybrid Workplace

Our hybrid workplace allows for flexibility aligned to role responsibilities and exceptional customer delivery. Location requirements for this role can be found above. 

Total Rewards 

We are proud to offer a variety of competitive, inclusive, and comprehensive total rewards that are designed to support the unique needs of our employees both inside and outside of the workplace.

In addition to offering competitive salary and variable compensation plans, equity options, and flexible health and wellness benefits, we are proud to offer generous PTO, Annual Company Holidays, Health Days, and Summer Fridays.

Employees' growth and development are supported throughout their career journey through informal and formal programs and activities, including access to LinkedIn Learning, regular People Leader training, and our internal Mentorship Program. 

Our Culture

At LogicGate, our culture and employee experience are grounded in our core values of Be as One, Do the Right Thing, Embrace Curiosity, Own It, Empower Customers, and Raise the Bar, which guide how we show up - for each other, our customers, and all we interact with.

We believe that the strongest teams are made up of individuals who bring their different identities, experiences, and perspectives to the table. We are committed to fostering an inclusive work environment where all employees’ differences are celebrated and everyone is encouraged to bring their authentic selves to work.

We encourage everyone to join one of our Employee Resource Groups (AAPI @ LogicGate, Pride at LogicGate, and Women in LogicGate) to participate in and contribute to conversations that foster an inclusive culture.

LogicGate also believes strongly in giving back to the communities in which we live and work. To enable our teams to give back, we offer paid volunteer hours and company-wide charitable activities supporting a variety of organizations and causes.

We are proud to have been recognized as a top workplace by Built In, Crain’s Chicago Business, the Chicago Tribune, and more. Visit our website to learn about our latest recognition.

Learn more about our culture here. 

Excited about LogicGate but not familiar with GRC? 

• GRC stands for Governance, Risk, and Compliance
• GRC professionals help their companies manage uncertainty, act with integrity, and stay on the right side of the law. 
• The GRC market is rapidly expanding with continuous growth opportunities. The current market size was valued at $50.5 billion in 2024 and is projected to reach $104.5 billion by 2031.

Join the core team at Eclipse, where we’re building an AI agent-first marketplace that connects intelligence with real-world tasks, starting with data collection and labeling. We are seeking a Data Scientist to establish the foundation for how our data is labeled, processed, and prepared for consumption by next-generation Large Language Models (LLMs). Your work will be critical in transforming our raw data collections into valuable, AI-ready datasets.

Qualifications 

• Proven experience as a Data Scientist or Machine Learning Engineer with a focus on data quality and preparation.
• Strong understanding of data labeling methodologies and hands-on experience with data annotation platforms and workflows.
• Demonstrated experience preparing datasets for training and fine-tuning Large Language Models (LLMs), including knowledge of techniques like tokenization, embeddings, and NER.
• Proficiency in Python and common data science libraries (e.g., Pandas, NumPy, Scikit-learn, spaCy, Hugging Face).
• Experience using APIs/SDKs to automate data annotation and active learning loops.
• Excellent communication skills, with an ability to create clear documentation for technical and non-technical audiences.

Responsibilities 

• Develop Data Labeling Strategies: Design and document a formal data annotation strategy, including clear, scalable, and efficient guidelines for labeling our data. Define and enforce quality metrics, including inter-annotator agreement.
• Optimize for LLM Consumption: Research, define, and prototype the optimal data formats, structures, and pre-processing steps required for fine-tuning and training LLMs on our datasets.
• Data Quality Analysis: Establish automated processes and metrics to analyze the quality of both raw and labeled data, providing feedback to improve our data collection and labeling workflows.
• Collaborate with Engineering: Work closely with the engineering team to guide the implementation of data processing pipelines and ensure the data infrastructure meets the needs of ML applications.

Nice-to-Haves

• Experience with audio data processing and relevant libraries.
• Familiarity with data annotation platforms and tools.
• Knowledge of modern MLOps principles and practices.
• Experience with large language model data curation and Reinforcement Learning from Human Feedback (RLHF) pipelines.

Join the Eclipse team!

Eclipse is building the fastest Ethereum Layer 2, powered by the Solana VM. Our general-purpose L2 combines the best of the modular stack without sacrificing UX or fragmenting liquidity. On top of this foundation, we’re building apps in-house and iterating quickly to find breakout consumer and AI experiences. We’re backed by top investors including Polychain, Tribe Capital, Placeholder, and DBA.

• Opportunity. We believe blockchains should be fast AND highly usable. You’ll do high-impact work to enhance Ethereum’s scalability, shaping the future of crypto
• Flexibility. We collaborate synchronously and asynchronously, across weekly all-hands meetings, Slack messaging, and quarterly in-person meetups
• Team. Our founding team has experience launching and scaling blue-chip projects such as dYdX, Uniswap, and zkSync. We’re backed by leading funds and leaders including Polychain, Tribe, Placeholder, DBA, Mustafa Al-Bassam, Tarun Chitra, Meltem Demirors, and others
• Culture. As an early member of our team, you’ll have a unique opportunity to help shape our culture. We value intellectual honesty, bias towards action, and believe every member plays a key role in achieving our ambitious goals
• Compensation. You’ll receive a competitive salary + equity + benefits package.

Eclipse Laboratories is an equal opportunity employer. We do not discriminate on the basis of race, color, religion, sex (including pregnancy, gender identity, and sexual orientation), national origin, age, disability, genetic information, veteran status, or any other status protected by applicable laws or regulations. All employment decisions are based on qualifications, merit, and business need.

JJanea Systems (USA) is a dynamic team of the best & brightest software engineering specialists and solutions innovators, from around the world. From kernel to cloud, we provide high-impact software development services to Fortune 500 companies.
We are urgently looking an exceptionally talented Senior Machine Learning Engineer to join our rapidly growing consulting team. In this role, you will have the opportunity to work at the cutting edge of the software industry and help work on the client's internal AI/ML practice, as well as utilize your LLM, Data Engineering, ML, and ML Ops skills while working with a team of highly skilled professionals in the AI/ML domain.

• To be considered for this position, you must have the following qualifications:

  • Bachelor's or Master’s degree in Computer Science or a related field
  • 4+ years of experience as a Software Engineer, Platform Engineer, ML Engineer, Data Scientist, AI Engineer, or Data Engineer
  • Flexibility in experience with different programming languages and willingness to adjust to project needs
  • Strong knowledge of Python
  • Knowledge of machine learning algorithms, data pre-processing methods, and ML frameworks (such as PyTorch, TensorFlow, Keras)
  • Experience with containers and Kubernetes in cloud environments (AWS, MS Azure, or GCP)
  • Familiarity with data-oriented workflow orchestration frameworks (KubeFlow, Airflow, Argo)
  • Understanding of software testing, benchmarking, and continuous integration principles
  • Ability to translate business needs into technical requirements
  • Excellent communication and problem-solving skills, with the ability to break down complex challenges and develop innovative solutions
  • Being self-motivated and adaptable, with the ability to work effectively in fast-paced, dynamic environment
    
    
  Ideal candidates will also have:
  • Familiarity with agent frameworks (such as Langchain, Langgraph, IllamaIndex)
  • Familiarity with developing RAG systems
  • Experience with Natural Language Processing (NLP)
  • Familiarity with monitoring tools (such as DataDog or Langfuse)
  • Any associate cloud certification (AWS preferred)
  Responsibilities:
  • Design scalable data pipelines and infrastructure for enterprise ML systems
  • Implement ML models and systems into production
  • Collaborate with data scientists and software engineers
  • Deploy scalable tools and services for machine learning training and inference
  • Evaluate new technologies to improve ML system performance and reliability
  • Apply software engineering best practices, including CI/CD, to ML development
  • Facilitate the development and deployment of ML proof-of-concepts
  • Review, refactor, optimize, containerize, deploy, version, and monitor ML models
  • Implement monitoring and alerting solutions to ensure the reliability and performance of machine learning systems
  • Optimize and automate the machine learning deployment process to ensure efficiency and reproducibility
  • Collaborate with cross-functional teams to troubleshoot and resolve issues related to machine learning deployments
  • Stay updated with industry trends and apply knowledge to drive innovation
  • Promote industry best practices and enhance team expertise
    
    
  Why join Janea? Because world-class talent deserves world-class opportunities. What we offer:
  • Competitive compensation with benefits, paid vacation, and sick leave.
  • The opportunity to work with a globally diverse team of top engineering talent on the industry’s toughest engineering challenges.
  • Ultra-flexible working conditions – we provide a generous office equipment allowance so you can work from home, we can also provide you with a desk at an office/coworking facility near you, or use both. No business travel necessary.
  • An enjoyable, start-up work environment, with excellent opportunities for professional growth and development.
  • Flexible working hours – as a remote-first company, our focus has always been on getting the job done well, not when or where it gets done.
   

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