Location

Remote

About the Role

You will own the end-to-end delivery of our core platform that powers our ATS, Video, Scheduling, and Telephony integrations along with our flagship AI features. Working in lockstep with Product and Design, you’ll move quickly to design, build, and refine features throughout the entire stack from data pipelines, database performance, and prompt engineering through the backend, and all the way to frontend interactions. You’ll focus on the performance and stability of the platform along with new product features to enable integrations, AI, and customer workflows. You will work on the output quality of AI features and make sure users get accurate, on-brand AI outputs fast. You’ll work on real features people use every day—things like:

• Automatic video recording and transcription.
• AI Notes and Summaries.
• Ensuring the platform can scale and reliably record, transcribe, and generate AI summaries for over 250,000 interviews per month.
• Generating insights and advanced AI insights quickly and reliably for all of our recorded interviews.
• Customizable interview summaries that enable customers to create fully personalized AI-generated summaries using their own structure and criteria.
• …and more

What You’ll Bring

• You have plenty of experience building across the stack in Python and Javascript/Typescript, especially building out the backend logic, data models, and architecture.
• You have a deep understanding and experience with data pipelines, distributed architectures, and scaling applications in high-scale environments.
• You think deeply about how customer facing features work for end users and can make decisions with user empathy.
• You might have real world experience building generative AI applications end to end, building prompt chains, eval harnesses, vector search, and more.
• You’ve worked with both structured (SQL) and unstructured data (raw text) and know how to transform them and utilize them together.
• You have product instincts and work well with design.
• You move fast and independently, but you know when to pair and when to pull others in.

About our team

• You’ll have the opportunity to work on high-impact projects in small, autonomous squads, with the flexibility to lead initiatives or focus as an individual contributor depending on your goals and interests.
• Our developer experience is thoughtfully designed, with fast CI (< 10 minutes), 1-click deploys, strong observability, and a clean codebase that enables you to move quickly and confidently.
• Our culture supports sustainable, focused work with fully remote roles, regular working hours, no-meeting Wednesdays, and flexible time off to recharge when needed.
• Our team is composed of smart, collaborative, and genuinely kind people, creating an environment where you can learn, grow, and do your best work.

Equal Employment Opportunity (EEO) Statement

Our company does not discriminate in employment on the basis of race, color, religion, sex (including pregnancy and gender identity), national origin, political affiliation, sexual orientation, marital status, disability, genetic information, age, membership in an employee organization, retaliation, parental status, military service, or other non-merit factor.

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. 

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. 

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.

What you will do: 

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

About the Job

As Splitero's Applied AI Engineer, you will own the identification, scoping, and delivery of AI-powered capabilities across our product and operations. You'll sit within the engineering organization but operate cross-functionally, partnering with product, operations, and business teams to identify where AI creates real leverage, then build it. Splitero sits at the intersection of financial services and property technology, and our product and engineering teams are at the center of that innovation every day. In this role, you'll work directly with our sales, processing, underwriting, closing, and servicing teams to identify, scope, and execute opportunities to streamline and automate their workflows as we scale. On the engineering side, you'll champion AI-first development, educate the team on emerging tooling, and lead technical initiatives that drive the organization forward.

You'll spend your time shipping working AI solutions into production by automating workflows, augmenting our product experience, and helping Splitero move faster and smarter as a business. You will have a strong understanding of when supervised AI outweighs the risk of full automation. You're as comfortable standing up a low-code n8n automation as you are writing clean code, and you know when each approach is the right one.

At Splitero, we move fast, and the ideal candidate thrives in that environment. You default to the simplest path to a working solution, prototype quickly using every tool available to you, and have the engineering discipline to know when something needs to be rebuilt properly before it goes to production.

Responsibilities:

• AI Discovery & Strategy
• Socialize AI capabilities, limitations, and roadmap across the org, acting as an internal resource and thought leader on what's possible.
• Maintain a prioritized backlog of AI opportunities across the business, triaging ideas from leadership, product, and operations into scoped, deliverable workstreams.
• Define AI initiatives end-to-end: problem framing, data requirements, build vs. buy decisions, and measurable success criteria.
• Stay current on the AI tooling landscape and recommend adoption where it meaningfully improves velocity, quality, or competitive positioning.
• Building & Delivery
• Build, integrate, and maintain AI-powered features and workflows, leveraging LLM APIs (OpenAI, Anthropic, etc.), RAG pipelines, and agentic frameworks.
• Develop automation workflows using low/no-code orchestration tools (n8n, Make) to deliver AI solutions rapidly without requiring full engineering cycles.
• Integrate AI capabilities into existing systems and codebases in close partnership with the product and engineering teams.
• Own the full AI development lifecycle, including prototyping, evaluation, deployment, monitoring, and iteration, with support from engineering, product, and operational teams.
• Cross-Functional Partnership
• Partner with product to translate user problems into AI-driven features and experiences.
• Embed within operations and business teams to identify workflow automation and efficiency opportunities.
• Collaborate with engineering to ensure AI integrations meet production standards for reliability, maintainability, and security.
• Document and communicate AI implementations clearly so the broader team can support and build on them.

Reporting Structure

• Reports directly to the VP of Product and Engineering
• Embedded within the product engineering team, works cross-functionally across Salesforce, product, operations, and business functions

The salary range for this position is $135,000 - $175,000. Within the range, individual pay is determined by job-related skills, experience, and relevant education or training.

About You

• 6+ years in software engineering with at least 2 years of focused experience building production AI or LLM-powered applications
• Hands-on experience with LLM APIs, prompt engineering, retrieval-augmented generation (RAG), and agentic workflow design. You are on the bleeding edge of the latest releases and advancements in AI platforms.
• Demonstrated experience evaluating, advocating, and operationalizing AI tooling across an organization
• Proficiency with low/no-code orchestration platforms (n8n, Make, Zapier) to prototype and deliver AI workflows rapidly
• Comfortable with AI-assisted development tools (Claude Code, Cursor, GitHub Copilot, etc.) to accelerate build cycles, with the judgment to write clean, maintainable code when it matters. You are not a vibe coder; you leverage your engineering background to balance speed with quality using AI-based tooling.
• Strong backend or full-stack engineering fundamentals; you integrate AI into real systems, not just prototypes
• Fluency in Python, TypeScript/Node.js, or similar; familiarity with PostgreSQL and cloud deployment platforms (AWS, Vercel, or similar)
• Experience with multi-agent frameworks (LangChain, LlamaIndex, or similar)
• Familiarity with vector databases, embedding pipelines, and evaluation frameworks for LLM outputs
• Self-directed and comfortable operating as a team of one. You run your own backlog and don't need a fully defined spec to get started and validate business use cases
• Strong communicator who can translate technical AI concepts for non-technical stakeholders across the org

Preferred:

• Experience in fintech, proptech, or real estate technology — particularly products handling sensitive financial data or consumer lending.
• Knowledge of SOC 2 or data privacy frameworks relevant to financial and personal data.

About Us

Millions of homeowners in today’s economy are sitting on substantial home equity they are unable to access due to rising interest rates and strict qualification requirements of traditional lenders. That means millions of homeowners can’t convert their hard-earned equity into cash to pay off debt, start a home renovation, or pad their retirement to better their lives.

Splitero co-founders Michael Gifford and David Zvaifler witnessed the problem firsthand throughout their real estate careers. They set out to create a win-win product that could help those homeowners access their home equity but not make monthly payments like traditional financing options. And thus, Splitero was born.

As part of our team, you will join our quest to revolutionize the real estate industry while helping families in need. We offer a suite of benefits designed to help you thrive in all areas of life.

• Fully Remote Team - Our remote-first culture allows us to hire the best people, regardless of location.
• OneTeam Culture - We foster a culture of transparency, innovation, and inclusivity, where every voice is heard and every team member is valued. We believe in celebrating our successes, doing the right thing, and helping each other so we grow as a team and as individuals. 
• Generous Resources - We want to ensure you are set up to do your best work. In addition to a solid tech stack, and access to any WeWork location, you will receive a monthly cell and internet stipend.
• Premium Healthcare - We offer comprehensive healthcare plans for you and your family, which employees are eligible for on their first day.
• Flexible PTO and Parental Leave - We offer a generous PTO and encourage employees to take time off to recharge. We're proud to offer a parental leave policy that allows you to welcome your new addition without worry.

We are a workforce composed of individuals with diverse backgrounds, abilities, minds, and identities. In keeping with our commitment to inclusion, we will ensure that people with disabilities are provided reasonable accommodations. If reasonable accommodations are required when applying, interviewing, or performing the essential functions of this position, please contact People Operations, at peopleops@splitero.com. 

About the Role

We’re looking for an ambitious AI Engineer to transform how our go-to-market team operates. San Francisco, Austin, or Lisbon are preferred locations where you can collaborate with team members, but the position is remote or hybrid. 

As the founding GTM engineer, you will architect and build the AI-powered systems that power our entire GTM motion, owning the technology stack, partnering with stakeholders to define the workflows, deploying AI agents and apps, and continuously improving how the company acquires, activates, and grows customers.

This is a highly hands-on role for someone who enjoys shipping systems, experimenting rapidly, and solving messy real-world problems with software.

Why This Role Matters

This role is a force multiplier for the entire company. You’ll build the infrastructure that allows the GTM team to move faster, learn faster, and scale without proportional headcount. You’ll help us:

• Turn GTM from a set of tools into a cohesive, intelligent system
• Scale workflows without scaling headcount
• Improve signal quality and timing for marketing and sales
• Increase learning velocity across the entire funnel
• Shape how an open-source, bottom-up product grows into enterprise adoption

What You’ll Do

Build & Automate the foundational GTM AI stack

• Design, build, and maintain AI systems across marketing, PLG, sales, and post-signup activation
• Own integrations and workflows across tools like CRM, marketing automation, product analytics, data warehouse, enrichment tools, and internal services
• Build internal tools and lightweight services that accelerate GTM teams
• Replace manual workflows with scalable, automated systems

AI-Powered Systems & Agents

Design and deploy AI-driven workflows and agents that augment GTM teams.

Examples include:

• Lead qualification, inbound lead routing, and enrichment
• Personalized lifecycle marketing and outbound messaging
• Sales assist tools for deal intelligence and account research
• Automated account insights, pipeline analysis, and deal lifecycle management
• User onboarding, activation, and expansion signals

You’ll continuously improve these systems using real performance data and feedback loops.

Growth: PLG + Sales-Assisted Motion

• Support a hybrid GTM model where open-source and self-serve users graduate into paid, sales-assisted customers
• Partner with Data & Growth to build systems that surface product signals (usage, intent, readiness) to marketing and sales teams at the right time
• Partner closely with Product & Marketing to turn usage insights into GTM leverage

Experimentation & Learning

Build the infrastructure that allows the GTM team to learn quickly and iterate with confidence.

• Design and run experiments across acquisition, activation, conversion, and expansion
• Build experimentation frameworks (feature flags, A/B testing, measurement systems)
• Instrument systems to capture reliable data and insights
• Rapidly iterate based on results, not assumptions

Feedback Loops & Continuous Improvement

Create tight feedback loops between users, product signals, and GTM actions.

• Partner with head of , accessible, and actionable across teams
• Turn qualitative and quantitative insights into system improvements
• Continuously optimize workflows, models, and automation based on real outcomes

What We’re Looking For

Core Skills

This is fundamentally an engineering role, not traditional GTM operations. We’re looking for someone who enjoys building systems, not managing tools.

• Strong engineering background (software, data, or growth engineering)
• Comfortable shipping production code (APIs, services, scripts, internal tools)
• Experience working with data pipelines, analytics, and experimentation frameworks
• Hands-on experience with AI/LLMs, prompt engineering, or agent-based systems

Collaboration & Ownership

• Ability to work cross-functionally with Product, Engineering, Marketing and Sales
• Comfortable operating with ambiguity and defining the problem as you go
• Strong communicator who can translate between technical and GTM stakeholders

Nice to Have

• Experience with open-source or developer-focused products
• Familiarity with CRM systems (e.g., Salesforce, HubSpot), CDPs, and marketing automation
• Experience building internal tools for sales or marketing teams
• Prior work in B2B SaaS, data, or AI-first companies

Janea 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 seeking an exceptionally talented Go-to-market Engineer (GTM Engineer) to join our rapidly growing consulting team. 
If you thrive at the intersection of growth, automation, engineering, and love turning campaign ideas into highly personalised outreach at scale, we encourage you to become part of our marketing team.

About the Role

As a Go-to-Market Engineer, you’ll own the entire outbound campaign lifecycle—from idea to execution. You’ll design, build, and run large-scale multi-channel campaigns across email and LinkedIn, ensure flawless infrastructure setup, and enrich and qualify data to create highly personalized messaging. This role is both technical and creative: you’ll be building systems, running automations, and writing detailed prompts for AI-driven personalisation while ensuring everything works at scale, emails consistently land in the primary inbox, and LinkedIn best practices are followed. 

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

• 2 years of experience in GTM, lead generation or outbound sales for custom software engineering or B2B professional services companies; 
• Deep expertise in email deliverability best practices and email infrastructure setup;
• Strong hands-on experience with Clay, Smartlead, Instantly, LinkedHelper, HeyReach, and CRM systems (e.g., Pipedrive);
• Familiarity with scraping tools and custom scripts for lead generation;
• Solid expertise in prompt engineering and familiar with AI-powered personalization workflows;
• Proven ability to run multiple large-scale campaigns in parallel;
• Strong automation skills, with the ability to design, implement, and maintain workflows that connect multiple GTM tools;
• Ability to identify opportunities for automation to reduce manual work and improve scalability;
• Ability to troubleshoot, refine, and optimize automated workflows to ensure they run reliably and efficiently;
• Being a strong systems thinker—organized, detail-oriented, and analytical. 
  
  

Ideal candidates will also have: 

• Certifications from Clay, Smartlead, or similar GTM tools.
  
  

Responsibilities: 

• Campaign Creation & Execution 

Own campaigns end-to-end: from building company/lead lists, enrichment, scoring, and messaging, to final execution. 

Orchestrate outreach across email and LinkedIn using Smartlead, LinkedHelper, HeyReach, and Clay. 

Build highly personalized value propositions that resonate with ICPs. 

• Email & LinkedIn Infrastructure 

Set up and manage domains, mailboxes, and sending infrastructure for large-scale campaigns. 

Apply email deliverability best practices to maximize inbox placement and engagement. 

Ensure LinkedIn outreach follows platform best practices for reach and safety. 

• Data Enrichment & Scraping 

Use scraping tools (or custom Python scripts if needed) to gather high-quality lead data. 

Run enrichments at scale and maintain data accuracy and cleanliness across systems. 

• AI & Prompt Engineering 

Build precise, detailed prompts for lead qualification, enrichment, and follow-ups. 

Use LLMs and agentic AI systems to create personalized campaign messaging. 

Continuously refine prompts and workflows to improve accuracy and relevance. 

• Outbound Infrastructure & Data Ownership 

Own and maintain the master contact database, ensuring accuracy, cleanliness, and structure. 

Manage and update the Do-Not-Contact (DNC) list across systems to safeguard compliance and avoid reputation risks. 

Monitor deliverability risks and proactively adjust infrastructure to maintain inbox placement and outreach safety. 

Oversee the overall health of outbound infrastructure, ensuring scalability and resilience.  

• Automation & Optimization 

Build workflow automations across the GTM stack to save time and scale campaigns. 

Run multiple campaigns simultaneously, ensuring deadlines and quality are met. 

Measure and optimize campaigns based on performance and conversion. 

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 marketing talent on the industry’s toughest marketing 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. 

#LI-DNI

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. 

Audio Editor for Dialogue / Audio Post-Production

Remote

We are seeking an experienced Dialogue Editor / Audio Engineer to prepare, clean, and optimize spoken-word audio for post-production delivery. This role requires strong technical judgment, critical listening skills, and a deep understanding of speech intelligibility, noise management, and real-world post-production workflows. The ideal candidate is fluent in iZotope RX & Pro Tools, understands the capabilities & limits of audio restoration, and consistently delivers natural-sounding, intelligible dialogue under deadline.

On a typical day, you will utilize your extensive experience in Izotope RX & Pro Tools to diagnose, flag, & edit audio to required specifications of various clients. You will operate in a cohesive team atmosphere while communicating flags, discoveries, & qualitative/quantitative audio statistics. This is a fast paced environment with minimal room for error. This position requires intense knowledge of recording stages - from sound source to mastered files, a keen ear for audio deficiencies, & a rigorous mindset for repetitive quality control. You will engage with technical teams on editing scenarios, theoretical audio engineering questions, and creative logic, while suggesting improvements to our prompt engineering and evaluation metrics.

A bachelor’s or master’s degree in Audio Engineering, Music Production, Acoustics, or a closely related field is ideal.

Required Skills

• Minimum 3+ years of professional experience in dialogue editing, audiobook, podcast, or spoken-word and sound post-production.
• Historical success & confidence in vocal cleanup using iZotope RX (standalone and plugin workflows) & Avid Pro Tools
• Familiarity with spoken-word loudness standards (e.g., Audible/ACX targets)
• In-depth knowledge of Spectograms
• Studio level listening/monitoring environment
• Ability to differentiate between performance issues & technical issues
• Identification of signal flow issues with Voice Talents
• Ability to work independently and deliver consistent, broadcast or release-ready dialogue
• Strong time management and attention to detail
• Excellent Collaboration Skills

• Taking direction from supervisors & management
• Communicating technical limitations clearly
• Making defensible processing choices

• Excellent critical listening skills with the ability to identify:

• Room tone inconsistencies

• Mic changes and phase issues
• Plosives, sibilance, & mouth noise
• Clipped or distorted dialogue
• Formant damage
• Intelligibility loss
• Noise masking issues
• Over-processing artifacts

We offer a pay range of $15-to-$30 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.

Project Title: Audio Editor for Dialogue / Audio Post-Production - Freelance AI Trainer Project

Employment type: Freelance / Contract

Workplace type: Remote

Are you a software engineer with deep infrastructure expertise and a systems-level mindset eager to shape the future of AI? Large-scale language models are increasingly responsible for reasoning about real-world systems, cloud architectures, and performance-critical infrastructure. With high-quality expert training data, tomorrow’s AI can better design, evaluate, and operate complex software systems at scale. That training data begins with you.

We’re looking for SWE Infrastructure Specialists fluent in JavaScript, TypeScript, and Python who specialize in systems thinking, software and infrastructure architecture, performance optimization, and quality engineering. You’ll challenge advanced language models on realistic infrastructure and platform scenarios involving cloud design, Infrastructure-as-Code abstractions, deployment workflows, scalability constraints, and failure modes. This work focuses on evaluating how models reason about architectural tradeoffs, abstraction layers, environment isolation, state management, and reliability across distributed systems.

On a typical day, you will converse with the model on infrastructure and platform engineering tasks using JavaScript, TypeScript, and Python, verify architectural soundness and logical correctness, assess code quality and testing strategies, analyze performance bottlenecks and deployment risks, capture reproducible failure cases, and suggest improvements to prompt design and evaluation metrics to strengthen model reasoning.

A bachelor’s, master’s, or PhD in computer science, software engineering, or a closely related technical field is ideal. Real-world experience in cloud platforms, infrastructure engineering, platform or DevOps roles, performance analysis, or QA practices strongly signals fit. Clear technical communication and the ability to clearly articulate system-level reasoning and tradeoffs are essential.

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

We offer a pay range of $80-to-$150 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: SWE Infrastructure Specialist (JS/TS/Python) – Freelance AI Trainer Project
Employment type: Contract
Workplace type: Remote