Experience Requirements:

• Strong experience with cloud infrastructure (AWS, GCP, or similar)

• Hands-on experience with Kubernetes, container orchestration, and infrastructure-as-code (Terraform or equivalent)

• Experience building and operating production systems with high availability and performance requirements

• Proficiency in at least one programming language used for platform development (Go, Rust, TypeScript, Python, or similar)

• Experience with observability stacks (Prometheus, Grafana, OpenTelemetry, etc.)

Other Requirements:

• Solid understanding of distributed systems, networking, and Linux internals

• Familiarity with CI/CD systems and release automation

• Good communication skills and ability to work effectively in a remote, async environment

• Fluent English

• Background in security best practices for cloud platforms

• Experience operating data-intensive or analytics-heavy platforms

• Hands-on use of AI coding tools (Claude Code, Cursor, Copilot, or similar)

• Contributions to open-source infrastructure or platform projects

Responsibilities:

• Designing and maintaining cloud-native infrastructure for a globally distributed analytics platform.

• Building internal platform tooling to improve developer velocity, observability, and deployment safety.

• Scaling multi-tenant systems that serve large volumes of analytical queries with strict latency requirements.

• Improving reliability, fault tolerance, and disaster recovery for Cube cloud platform.

• Operating Kubernetes-based environments and evolving our deployment and release pipelines.

Experience Requirements:

• 5+ years of experience in Sales Engineering, Solutions Consulting, Solutions Architecture, or a closely related technical customer-facing role

• Proven track record supporting SaaS sales cycles with complex technical products — ideally in the data, analytics, or AI infrastructure space

• Deep fluency in the modern data stack: cloud data warehouses (Snowflake, Redshift, BigQuery), data transformation tools, semantic or metrics layers, and BI platforms

• Strong SQL skills and a solid grasp of data modeling concepts

• History of hitting or exceeding quota in a technical sales role, ideally with recognition for performance

Other Requirements:

• Comfortable navigating full sales cycles — from discovery and technical validation to security reviews and executive presentations

• Exceptional communicator who can engage engineers, data leaders, and C-suite stakeholders with equal clarity and credibility

• Entrepreneurial mindset: thrives in fast-moving startup environments and solves problems proactively

• Hands-on experience with semantic or metrics layers — Cube, LookML, MetricFlow, dbt Semantic Layer, or similar

• Familiarity with legacy OLAP technologies (Microsoft SSAS, Oracle Essbase, SAP BW)

• Proficiency in at least one high-level programming language: Node.js, Python, Ruby, Java, Scala, or similar

• Experience building or contributing to solutions that integrate AI agents, LLMs, or agentic workflows with data infrastructure

• Background in analytics consulting or data engineering

• Active presence in the data community: published content, conference talks, open-source contributions, or a strong professional network

Responsibilities:

• Become the go-to subject-matter expert on semantic layers, data modeling, performance tuning, and modern data and AI stacks — including how Cube enables Agentic Analytics workflows.

• Partner with Account Executives to deliver tailored demos, technical deep dives, and proof-of-concept engagements that translate complex data challenges into compelling, elegant solutions.

• Own the full technical customer relationship: requirements gathering, solution architecture, integrations, and success criteria for pilots and POCs.

• Translate enterprise data challenges into solutions that leverage Cube's semantic layer alongside BI tools, data warehouses, AI agents, and governance systems.

• Capture and document customer feedback to directly influence the product roadmap and partner integration strategy.

Experience Requirements:

• Hands-on engineer, comfortable owning and shipping production code

• Experience building data, analytics, or AI products

• Background in startups or scale-ups with hybrid or fast-evolving roles

• Practical experience with AI technologies, LLMs, or agent-based systems

• Familiarity with modern backend architectures, cloud platforms, or distributed systems

Other Requirements:

• Strong product mindset — thinking in terms of user value, outcomes, and what's actually worth building

• Genuinely excited about AI, agents, and the data and analytics space

• Comfortable with ambiguity and enjoy shaping problems as much as solving them

• Strong communicator who thrives in a remote, async team

• Fluent in English

• Contributions to open-source or public technical projects

Responsibilities:

• Take product ideas from concept to production — owning both the 'what' and the 'how.'

• Build, prototype, and ship core product features, with a focus on AI- and agent-powered experiences.

• Turn user needs and business goals into pragmatic, working software.

• Explore practical AI use cases and turn the most promising ones into real product value.

• Make fast, sound technical decisions in close partnership with engineering and product.

Benefits:

• Competitive salary and generous stock options in a growing company

• Unlimited PTO — we actually use it

• Remote-first culture with coworking space stipend if you prefer not working from home

• Team offsites several times a year (locations rotate between the US and Europe)

• Professional development budget — training courses, books, conferences

Experience Requirements:

• 5+ years in a customer-facing role at a data, analytics, or developer-tools company (CSM, technical account manager, solutions consultant, or similar)

• Strong SQL skills — you can write queries with window functions, CTEs, and cohort logic, and you can read someone else's SQL and spot what's wrong

• Experience working with technical stakeholders and executive stakeholders in the same account

• Track record of managing renewals and driving account growth in a SaaS environment

• Familiarity with the modern data stack: cloud data warehouses, transformation tools (dbt), and BI/analytics tools

Other Requirements:

• Ability to run a QBR that a data leader would actually find valuable — business narrative, not just metrics

• Excellent written and verbal communication

• Based in the US with availability for overlap with US business hours

• Experience with Cube or semantic layer concepts

• Background in analytics engineering, data engineering, or BI

• Familiarity with embedded analytics use cases and multi-tenant architectures

• Experience with API-first or developer-tool products where the buyer is technical

• Understanding of AI/LLM integrations in the data stack

• Comfort with light data modeling, YAML/code-based configuration, or git workflows

Responsibilities:

• Own customer outcomes. Manage a portfolio of mid-market and enterprise accounts end-to-end — from onboarding through renewal.

• Run strategic QBRs. Prepare and deliver quarterly business reviews that go beyond usage dashboards.

• Get technical. Understand how customers have modeled their data in Cube, diagnose performance issues, and advise on best practices.

• Be the voice of the customer internally. Translate customer feedback into actionable product insights.

• Drive adoption of new capabilities. Cube's platform is evolving fast — Analytics Chat, embedded agentic analytics, MCP integration, workbooks and dashboards.

Experience Requirements:

• Experienced building multi-threaded campaigns across mid-market and enterprise organizations

• Enterprise sales experience, ideally with exposure to (or genuine interest in) the data/analytics industry

• Familiar with sales prospecting tools such as Attio, Apollo, and LinkedIn Sales Navigator

Other Requirements:

• A highly motivated, disciplined self-starter with strong interpersonal skills and excellent written, verbal, listening, and presentation skills

• Metrics-driven, with an analytical approach to solving business problems and reviewing and reporting on KPIs

• Creative and strategic in how you generate qualified leads

• Comfortable interacting with stakeholders across multiple departments

• Hiring for this role in the United States

Responsibilities:

• Hit a quarterly target of qualified meetings sourced from our range of inbound channels — paid and organic, free (PLG) signups, and open-source users.

• Build outbound campaigns that drive interest, user signups, and qualified meetings for sales.

• Continually optimize target audiences, sales cadences, and pitches for the best results.

• Run outreach across a mix of traditional and new channels — email, phone, LinkedIn, AI — and keep testing new methods and messaging.

• Improve GDR efficiency by bringing in and implementing new tools.

Benefits:

• Offers Equity

Experience Requirements:

• 10+ years of B2B SaaS product marketing experience, including senior leadership roles

• Deep experience in developer tools, AI, security, DevOps, infrastructure, or technical enterprise software

Other Requirements:

• A record of positioning complex products in crowded markets and moving organizations beyond feature-led messaging

• Proven launch and enablement leadership that drove measurable adoption, pipeline, retention, expansion, or revenue

• Credibility with engineering, security, product, sales, and executive audiences

• Experience supporting both product-led growth and enterprise go-to-market motions

• Exceptional writing, storytelling, and analytical judgment grounded in customer research, product data, and competitive evidence

Responsibilities:

• Own positioning, messaging, segmentation, personas, use cases, and differentiation across CodeRabbit's workflows

• Lead the category shift from human-centric code review to comprehensive code governance and Agentic Change Management

• Build and lead launches end to end—from customer insight and product framing through packaging, enablement, content, PR, community, adoption, and field follow-through

• Translate technical capabilities and evidence into compelling value stories for developers, engineering leaders, security teams, and executive buyers

• Equip Sales and Customer Success with demos, talk tracks, competitive guides, PoV materials, executive narratives, ROI frameworks, and objection handling

Experience Requirements:

• 5–8+ years of full-cycle technical recruiting, ideally at high-growth startups, developer-tools companies, or teams scaling engineering headcount quickly

Other Requirements:

• A proven history of landing senior engineers, data scientists, ML practitioners, and technical PMs in genuinely competitive markets

• Standout sourcing chops — real fluency with GitHub, LinkedIn Recruiter, Boolean search, and creative approaches

• Enough technical fluency to talk credibly with engineers about their work, read role-fit signals, and judge candidate quality well past the resume

Responsibilities:

• Drive full-cycle recruiting across engineering, data science, ML, product, and technical operations

• Sit down with hiring managers and technical leads to pin down what 'excellent' means for each role

• Build interview loops that are sharp and repeatable, testing for genuine technical depth alongside judgment

• Hunt for engineers, data scientists, and technical PMs through advanced sourcing across GitHub, LinkedIn, and technical communities

• Create and refine interview frameworks, assessment methods, and hiring rubrics that hold up as teams grow

Benefits:

• Offers Equity

Education Requirements:

• Degree in Computer Science, Engineering, or related field, or equivalent practical experience

Experience Requirements:

• 7+ years building full stack applications in production environments

Other Requirements:

• Proficiency in React, TypeScript, and modern web development practices

• Strong experience with Node.js (or similar), APIs, and distributed systems

• Familiarity with cloud infrastructure (AWS/GCP), containers, CI/CD, and observability

• Strong fundamentals in testing, code quality, and version control

• Must have strong experience using development tools like Cursor, Claude Code, or Codex and strong familiarity with various models

Responsibilities:

• Design and build full stack features across frontend, backend, and infrastructure

• Develop scalable APIs and services that support AI-driven workflows

• Create intuitive, high-performance user interfaces for developer tools

• Collaborate with ML engineers to integrate AI models into product experiences

• Own projects end-to-end, from concept through deployment and iteration

Benefits:

• Competitive salary, equity, and benefits

• Professional development opportunities

Experience Requirements:

• At least 3+ years of experience in customer success or account management

Other Requirements:

• Technical competency to understand CodeRabbit’s software and build strong relationships with highly technical prospects and key business stakeholders

• Strong knowledge of the customer success space, including experience with negotiations and procurement processes

• Comfortable and proficient with various sales methodologies such as MEDDPICC, SPICED, and Command of Message

• Familiarity with modern software development practices, version control systems, and the software development ecosystem, e.g. Git, GitHub, CI/CD, VS Code, Cursor

• Ability to travel about 25% of the time to meet with customers

Responsibilities:

• Build strong, meaningful relationships with our customers and proactively seek to understand their business objectives and expectations

• Drive engagement and adoption throughout the full customer journey

• Own a book of business to include renewals and expansion opportunities (for customers with <5,000 employees)

• Become a product expert and understand all components of CodeRabbit

• Educate customers on the best product usage, ensuring they maximize the value out of it

Benefits:

• Offers Equity

Education Requirements:

• Degree in Computer Science, Engineering, Artificial Intelligence, or related field, or equivalent practical experience

Experience Requirements:

• 5+ years applying ML or LLM-based systems in real-world production environments, with at least 2 years of industry experience focused on generative AI

Other Requirements:

• Strong programming skills in TypeScript and Python

• Experience with tooling such as LangChain, LlamaIndex, OpenAI APIs, or vector databases like Pinecone or Lancedb

• Strong skills in prompt engineering

• Ability to extract insight from telemetry, logs, user signals, and structured feedback

• Experience working across product, engineering, and design to deliver production-grade systems

Responsibilities:

• Design and optimize LLM-based systems for high-quality, context-rich code reviews

• Build and refine agentic workflows that reason across multiple steps and contexts

• Develop and maintain knowledge base and retrieval pipelines (e.g., chunking, embeddings, semantic search)

• Deploy generative AI models and pipelines into production and monitor performance

• Collaborate across teams to ensure that AI outputs align with user needs and product goals

Benefits:

• Flexible work schedule

• Unlimited PTO

• Competitive healthcare

• Gear stipends

Experience Requirements:

• 6+ years of experience as a product designer with solid UX judgment

• Experienced building and governing design systems at scale

Other Requirements:

• Exceptional VisD skills with an eye for typography, color, spacing, detail, and motion craft

• Technically fluent: comfortable working close to code

• Decisive in ambiguity and principled in defending decisions

Responsibilities:

• Define the token architecture, component structure, and theming model for the system to flex across products and surfaces

• Establish the standards, documentation, and contribution model that keep the system coherent

• Work hand-in-hand with frontend engineers to ensure the system is implemented faithfully

• Bring meticulous visual and interaction craft, including motion and micro-interaction detail, to every component and pattern

• Build artifacts, documentation, and relationships to drive system adoption across teams

Education Requirements:

• A PhD or equivalent research experience

Experience Requirements:

• 2–3+ years of hands-on experience applying generative models at scale

• Expertise in diffusion models and awareness of the latest efficiency techniques

• Experience in multimodal generation — spanning video, audio, and language

• Proven innovation in long-video generation and/or audio generation

• Track record of publications in top-tier venues (CVPR, NeurIPS, BMVC, ICASSP, etc.)

Other Requirements:

• Excellent programming skills — fluent in PyTorch and GPU-optimized workflows

• Experience leading research activities or mentoring teams

• Skills in 3D graphics, Gaussian splatting, or large-scale training setups (nice-to-have)

• Broad exposure to generative AI models beyond your specialty (nice-to-have)

• Familiarity with software development best practices (nice-to-have)

Responsibilities:

• Lead research efforts on audio-visual generation for avatars (Neural Avatars, Talking-Heads), with a focus on conversational settings

• Design models that are coupled with conversation flow — capturing and generating verbal + non-verbal signals in sync

• Drive innovation in diffusion models, long-video generation, and audio-visual modeling

• Translate research into production by partnering with Applied ML and engineering

• Mentor researchers, set research directions, and publish impactful work

Benefits:

• Flexible work schedule

• Unlimited PTO

• Competitive healthcare

• Gear stipends

Other Requirements:

• Holistic thinker who understands user journeys

• Ability to craft high-fidelity web experiences, cinematic marketing assets, and narrative-driven campaigns

• Strong understanding of product mindset and IA, messaging logic, and typography

Responsibilities:

• Lovingly and relentlessly evolve the soul and spirit of Tavus across website, social presence, and sales collateral

• Act as the ethos bridge between Marketing and Product

• Use your product mindset to optimize high-traffic marketing surfaces and drive conversion

• Spend ~20% of your time integrated with the product team contributing to design systems and high-visibility moments

• Continually push the ceiling for what quality looks like at Tavus

Education Requirements:

• A PhD (or near completion) in a relevant field, or equivalent research experience

Experience Requirements:

• Hands-on experience with Large Multimodal Models and a strong foundation in generative (language) models

• Experience in fine-tuning/adapting VLMs for control, conditioning, or downstream tasks

• Solid background in deep learning and foundation modes

Other Requirements:

• Strong PyTorch skills and comfort building deep learning pipelines

• Knowledge of large-scale model training and optimization (nice-to-have)

• Experience in duplex-conversational model (nice-to-have)

• Broader understanding of generative AI across modalities (nice-to-have)

• Exposure to software development best practices (nice-to-have)

Responsibilities:

• Conduct research on Large Multimodal Models in the context of Conversational Avatars (e.g. Neural Avatars, Talking-Heads)

• Develop methods to model both verbal and non-verbal aspects of conversation, adapting and controlling avatar behavior in real time, with low-latency

• Experiment with fine-tuning, adaptation, and conditioning techniques to make AudioVisual Multimodal Models more expressive, controllable, and task-specific

• Partner with the Applied ML team to take research from prototype to production

• Stay up to date with cutting-edge advancements — and help define what comes next

Benefits:

• Flexible work schedules

• Unlimited PTO

• Competitive healthcare

• Gear stipends

• Relocation support offered

Experience Requirements:

• Strong experience in deep learning using PyTorch

• Hands-on experience with model optimization and compression, including knowledge distillation, pruning/sparsification, quantization, and mixed precision

• Understanding of efficient architectures such as low-rank adapters

• Experience working with large models and datasets in cloud environments

Other Requirements:

• Strong understanding of inference performance and GPU/accelerator fundamentals

• Strong Python coding skills and reliable research engineering practices

• Ability to read ML papers, reproduce results, and adapt ideas

• Clear communication and collaboration skills

• Familiarity with TensorRT, ONNX Runtime, TVM, Triton, or XLA (preferred)

Responsibilities:

• Take cutting-edge research models and make them fast, efficient, and production-ready using sparsification, distillation, and quantization

• Own the optimization lifecycle for key models: define metrics, run experiments, and benchmark trade-offs across latency, cost, and quality

• Partner closely with researchers and engineers to turn new ideas into deployable systems

Experience Requirements:

• Senior track record of setting direction, owning decisions, and delivering

• Experience building real-time systems (video, audio, or model inference) with a millisecond latency budget

Other Requirements:

• Fluent in Python, with real depth in concurrent programs (asyncio, multiprocessing, event loops, GIL, shared memory)

• Ability to explain complex things clearly

• Proactive, autonomous, and energized by unfamiliar problems

• Experience with GPUs and GPU management (nice-to-have)

• Deep experience with video streaming over WebRTC (nice-to-have)

Responsibilities:

• Take product priorities that start out loosely defined and turn them into a spec, an architecture, and shipped features end-to-end

• Partner with Research to bring state-of-the-art real-time models into CVI

• Proactively fix flaky processes or slow paths

Experience Requirements:

• Proven track record in both 0→1 and 1+

Other Requirements:

• Opinionated and default to action

• Strong conviction, seeks feedback, and executes bringing the team along

• Exceptional organization and communication skills

• Clarity of written thought

Responsibilities:

• Work in massive ambiguity

• Help run and define company-wide product management

• Own customer outcomes end to end across entire customer journeys

• Earn the respect of the engineering team by speaking their language and inspiring

• Move extremely fast with a strong bias for execution

Education Requirements:

• Master's degree in data analytics, business analytics, or other closely related field

Experience Requirements:

• 1 year of related experience in data analytics

Responsibilities:

• Formulate hypotheses and test them using rigorous analytical methodologies and diverse frameworks

• Conduct advanced statistical analysis, machine learning, and data mining to drive product insights

• Develop and implement predictive models to support product strategy and decision-making

• Define key performance indicators (KPIs) and develop dashboards to monitor product performance

• Conduct A/B testing and other experimental methods to measure the impact of product changes

Benefits:

• Offers Equity

Benefits:

• Offers Equity