What You Bring

• Proven Track Record in Large Deals: 7+ years managing enterprise sales cycles with experience closing $5M–$20M+ annual agreements spanning multiple concurrent projects.
• Expert in Multi-Threaded Sales: Demonstrated success engaging across research leaders, engineering stakeholders, procurement teams, and C-suite executives.
• Consultative & Strategic Approach: Adept at translating technical needs (AI safety, evals, data quality, benchmarks) into commercial frameworks that resonate with business and technical leaders alike.
• Operational Rigor: Ability to manage complex deal structures, ensure visibility across 20+ active workstreams, and coordinate with internal delivery and product teams to ensure flawless execution.
• Domain Expertise: Experience selling AI, ML, or human-data services to advanced research orgs and technical decision-makers.
• Full-Cycle Deal Leadership: Skilled in qualification, solution design, proposal building, negotiation, procurement navigation, and customer success alignment.
• Executive Communication: Excellent written and verbal communicator with the ability to craft compelling narratives for both technical and business stakeholders.

What You'll Bring

• 8+ years of experience in data science, analytics, or a related AI field
• Strong SQL and Python skills; experience with data visualization tools (e.g., Looker, Tableau, Metabase) for data storytelling
• Experience designing and running A/B tests or correlational analyses
• Familiarity with LLM evaluation methodologies or AI quality assurance
• Experience working with research teams or supporting program evaluation
• Clear communication skills for translating data into insights for non-technical stakeholders

Nice to Have

• Experience in education, workforce development, or public sector contexts
• Familiarity with FERPA, COPPA, or student data privacy requirements
• Experience with knowledge graphs or RAG systems
• Background in qualitative research support or mixed-methods evaluation

ABOUT YOU:

• 6–15 years of experience in technical, customer-facing, or product leadership roles, with a proven track record of driving projects from 0 to 1 and delivering measurable business impact
• Experienced in managing enterprise customer deployments, integrations, and cross-functional initiatives, balancing customer urgency with long-term scalability
• Commercially minded, you understand how successful deployments unlock renewals, expansions, and customer advocacy
• Strong analytical skills who defers to using data to inform decisions, define success metrics, and drive continuous improvement
• Exceptional project management and organizational skills — able to simplify complexity, prioritize competing initiatives, and hold teams accountable while setting clear strategic direction
• Relentless ownership mindset: no task is too small, hands-on when needed, and equally skilled at leading teams, coaching talent, and partnering with executives
• Working knowledge of APIs, data flows, and light-coding experience (JavaScript, Python, or similar)

Tech Stack:

• Infrastructure/Systems: AWS (ECS, Bedrock, Cognito, etc.), Docker, Github Actions
• Languages/Frameworks: Python, Django, Celery, django-ninja, django-tenants
• Database/Storage: PostgreSQL (AWS RDS), S3
• Development Tools: Github, Jira, CoderabbitAI, Tusk, Claude

What we're looking for:

• 5+ years experience building and deploying applications in production in a backend engineering / data engineering capacity
• Relevant experience with developing LLM-based systems for ingesting and evaluating unstructured records for industry-specific use cases and integrating them with user-facing features
• Deep understanding of the limitations of using LLMs and the best practices for using them for reliable, consistent, and accurate outputs
• Customer obsessed and motivated to build a best-in-class model for behavioral health clinical assessments in the healthcare space
• A collaborative team player with a focus on delivering measurable results

Requirements

• You have designed and built scalable, general-purpose search or retrieval systems end-to-end.
• You bring deep expertise in AI-powered search methodologies, including LLMs, embeddings, vector databases, and retrieval-augmented generation.
• You have a strong understanding of indexing, query processing, and ranking architectures.
• You’re a hands-on engineer with experience leading or scaling systems and teams in fast-moving environments.
• You’ve worked within or closely alongside world-class AI/search organizations (e.g., OpenAI, Anthropic, Perplexity, xAI, Google DeepMind, etc.).
• You’re proficient in Python, SQL, Docker, and microservices, with familiarity in function/tool calling from an LLM.
• You communicate with clarity and thrive in a highly collaborative, cross-functional setting.

Nice to Haves

• Experience building retrieval or ranking systems specifically for publisher or adtech ecosystems.
• Familiarity with distributed vector search systems or hybrid retrieval frameworks.
• Prior startup or early-stage product experience—comfortable building with ambiguity and speed.
• Background in reinforcement learning, personalization, or recommendation systems.

Requirements:

• Bachelor’s Degree in Computer Science, Data Science, or related field (or equivalent experience).
• 4+ years of experience in software engineering, data engineering, machine learning, or AI development.
• Strong proficiency in Python (experience with Ruby is a huge plus).
• Hands-on experience building applications with LLMs (OpenAI, Anthropic, Bedrock).
• Experience with Agentic Frameworks (CrewAI, AutoGPT, LangGraph, etc.).
• Experience designing data workflows with Airflow or similar orchestration tools.
• Experience building systems using Test-Driven Development (TDD), building tested, secure, scalable applications.
• Ability to communicate complex technical AI concepts to non-technical stakeholders.

• 1–3 years shipping production software in real-world systems
• Proficiency in TypeScript and/or Python
• Some exposure to LLM APIs (OpenAI, Anthropic, Gemini) or AI tooling
• Familiarity with retrieval pipelines, RAG concepts, or vector databases is a plus
• Experience with React and Postgres is helpful but not required
• Comfortable working in ambiguity with direction from senior engineers

What We’re Looking For

• 7–10+ years of experience as a Data Scientist, Applied Scientist, or Machine Learning Engineer, with ownership of production systems.
• Experience in security, identity, fraud, or risk modeling domains.
• Strong background in statistical modeling, machine learning, and applied decision systems.
• Experience designing and shipping ML- or AI-driven product features used by customers.
• Experience applying ML or AI to decision-making systems that influence user workflows or automated outcomes.
• Comfortability working within the GCP stack, particularly big data services, such as Dataproc (pyspark), Dataflow (Apache Beam), PubSub (Apache Kafka), data lakes (storage, partitioning, searching). Also, experience with SQL, Python, and related Data Science libs (such as scikit-learn, pytorch, GCP integrations, etc).
• Experience designing or contributing to agent-like or automated workflows, including reasoning about task decomposition, tool usage, or control flow.
• Demonstrated ability to design guardrails and human-in-the-loop mechanisms for automated or AI-assisted actions.
• Experience operating ML or AI systems post-launch, including monitoring behavior, iterating based on feedback, and addressing reliability or trust issues.
• Familiarity with LLMs and agent-based approaches, with practical awareness of reliability, safety, and evaluation considerations.
• Ability to balance automation, explainability, and user trust in customer-facing systems.
• Experience partnering closely with Product and Engineering to deliver customer-facing capabilities.
• Strong written and verbal communication skills.

In this role, you will:

• Design, build, and operate LLM-driven systems that prioritize and drive SEO work
• Encode human expertise into structured, repeatable AI workflows
• Architect and optimize complex LLM pipelines for accuracy, reliability, and cost
• Build evaluation frameworks that measure quality and real-world performance
• Collaborate closely with engineers, designers, and Growth Leads to integrate AI into execution
• Ship quickly, then iterate based on feedback from production usage
• Work primarily across LLM-driven systems, data pipelines, and AI-enabled services, using Python, TypeScript, and C#, deployed on Google Cloud with modern foundation models

Minimum Qualifications

• Strong experience building production AI or machine learning systems
• Hands-on experience working with LLMs beyond basic API usage
• Solid understanding of NLP concepts such as embeddings, retrieval, and generation
• Experience owning systems end-to-end, including design, implementation, and iteration
• Comfort operating in ambiguous problem spaces and making sound technical tradeoffs

Preferred Qualifications

• Deep expertise in NLP or applied machine learning
• Strong mental models of transformer-based architectures and modern language models
• Experience designing evaluation methodologies for AI systems
• Familiarity with probabilistic modeling, algorithms, or statistical inference
• Experience translating domain expertise into scalable software systems
• A high bar for correctness, reliability, and operational quality

What You'll Bring:

• 5+ years of background in research, specializing in AI/ML, deepfake, or authentication
• Experience with data analysis, detection models, computer vision, or cognitive science
• Excellent writing and communication skills
• Intellectual curiosity about truth, identity, and media in the AI era
• Ability to work independently and think creatively across disciplines

What you bring:
You are a product-minded builder with a proven track record of architecting & building complex web applications
You have deep expertise with complex database schemas
You embrace building software in a AI-first environment
You’re familiar with the demands of building products in a startup environment and comfortable with ambiguity
You are deeply passionate about putting your skills to work to address climate change and eager to join an ambitious, fun-loving, and radically caring team that imagines the world as it should be rather than as it is
You’ve been building software for at least 5 years

Skills that would make you stand out:

Prior experience building AI-powered software
Curiosity about construction and the built environment
Experience building data-driven products
Proven ability to architect complex applications that remain maintainable as requirements evolve
Knowledge of construction modeling software, such as Revit
Deep Ruby on Rails expertise

Some of the things you’ll be working on:

Using ML / AI to rapidly automate workflows in the real estate & construction industries
Collaborating with UX, Product, Research and our founding team to build the product.
Architecting the platform that will prevent the emission of millions of kilograms of CO2.
Designing, building, testing, deploying and operating a rapidly scaling web application using Ruby on Rails, TypeScript & React
Ingesting 3D models and PDF construction documents of buildings to measure and optimize the carbon related to the construction of the building.
Evolving our database of building materials, manufacturers, commercial real estate projects and their carbon footprints, material health impacts, costs, and more
Developing integrations with other software platforms across construction, design, procurement, and reporting; e.g., Procore, Autodesk Construction Cloud, and carbon accounting platforms

Requirements for Success:

• 7+ years in AI engineering, machine learning, or automation. (SaaS, ERP, or supply chain technology environments preferred)
• Bachelor’s degree required (Master’s preferred) in Computer Science, AI, Data Science, or related field.
• Some travel may be involved - up to 15%
• Experience defining, executing, and scaling AI strategies across complex global organizations from the ground up
• Previous success in accelerating software delivery with AI-augmented SDLC: implementation tools and automated testing frameworks to improve development velocity and quality
• Exposure to AI use cases across multiple domains (e.g., customer onboarding, customer support, operations).
• Familiarity with LLMs, generative AI, and prompt engineering
• Strong programming in Python (additional experience with Java, C++, or similar is a plus).
• Hands-on expertise with AI/ML frameworks (TensorFlow, PyTorch, Scikit-learn).
• Proven experience deploying models via APIs, Docker, Kubernetes, and cloud-native ML platforms (AWS SageMaker, Azure ML, or GCP Vertex AI).
• Solid understanding of MLOps, data engineering, and software architecture principles.
• Strategic, innovative, and curious — with a passion for driving measurable business outcomes through technology.
• Exceptional communication, influence, and problem-solving abilities. Able to translate technical concepts into business impact.

What You'll Do

• Own and evolve the Search Ads relevance stack—spanning query understanding, targeting, candidate generation, multi-stage ranking, and calibration—while meeting stringent latency and reliability goals.
• Design and productionize ML models that improve sponsored-result relevance and personalization, using a blend of unstructured signals (text/images where applicable), LLM-based representations, and structured marketplace features.
• Partner closely with engineering and product to connect relevance improvements to ads marketplace outcomes (e.g., conversion, long-term retailer experience, advertiser ROI), using rigorous offline evaluation and online experiments.
• As an early member of the Ads Data team, help define its roadmap and technical culture, leveraging deep product intuition to shape what ads should be—not just how they’re built.
• Work in a fast-paced, collaborative environment with team members who’ve shipped ML at top tech companies (e.g. Uber, Airbnb, Meta, Amazon, Pinterest).

Qualifications

• 4+ years of experience building and shipping ML systems in production, with meaningful experience in search, recommendation, or ads ranking/retrieval.
• Hands-on experience with modern deep learning tooling (e.g., PyTorch) and familiarity with vector search / embedding-based retrieval concepts (e.g., Faiss, ScaNN, Pinecone).
• A strong track record of productionizing models that blend LLMs (e.g., BERT / GPT-class) with structured features to drive relevance and personalization.
• Product-focused mindset and a bias toward execution—moving quickly from research to measurable user and business impact.
• Strong communication skills and the ability to work with others in a closely collaborative team environment

Great to Haves

• Highly recommended: Master’s or PhD in Computer Science, Statistics, or related STEM fields
• Ability to quickly implement state of the art algorithms from an academic paper

Role and Responsibilities:

• Develop performant, scalable, and high quality APIs and backend processes for SaaS platform, with a strong emphasis on LLM integration.
• Collaborate with cross-functional teams to implement new features and refine existing ones, particularly those involving AI/LLM capabilities.
• Provide feedback on roadmap and features for your team, contributing to the strategic direction of  AI/LLM initiatives.
• Ensure code quality and compliance through thorough reviews, unit testing, and adherence to best practices for LLM-powered applications and engineering.
• Optimize application performance and scalability to meet user demands, especially for LLM inference and data processing.
• Stay informed about emerging AI/LLM technologies, prompt engineering techniques, and industry trends.
• Troubleshoot and resolve production issues, ensuring performance, reliability, and scalability of LLM-driven features.

Technologies:

• OpenAI, Vertex, other public LLM APIs
• Django/Python
• PostgreSQL
• GCP

REQUIREMENTS: THE VALUE YOU WILL BRING!

• Experience shipping LLM pipelines including preprocessing, prompt optimization, output validation, and fallback mechanisms
• Experience with production use of LLM APIs (e.g., OpenAI, Gemini)
• Experience building systems to measure model performance, detect drift, and ensure output quality in production environments.
• Proficiency in prompt engineering and/or have developed systematic approaches to prompt design
• Proficiency with Python and Django (or similar frameworks)
• Strong collaboration and communication skills in cross-functional environments
• Bachelor’s degree in computer science or related field, or equivalent work experience
• 3+ years of experience as a Software Engineer

Nice to Have Experience, but Not Required:

• Docker/Kubernetes
• CI/CD pipelines (GitLab CI, Github actions, Jenkins, etc.)
• Working in highly regulated industries (e.g., healthcare, pharma, fintech)
• Experience with async tasks and workflows (such as Celery)
• Shipping production code for B2B software products
• Relational databases (PostgreSQL preferred)

The Mandate

• Architect Product Artistry: Bridge the gap between complex AI research and seamless user experiences. You will transform raw model capabilities and complex workflows into polished products that feel like magic to millions of creators.
• Guardian of Taste: Act as the final filter for aesthetic quality. You will ensure every feature meets an uncompromising standard for rhythm, composition, and visual harmony.
• Rapid Prototyping: Lead through execution by building functional proofs-of-concept. You will work directly with APIs and codebase to validate hypotheses before they move to full-scale engineering.
• Strategic Market Pioneering: Identify latent creator needs and competitive gaps long before they become industry consensus. You will prioritize bold, high-impact bets over safe, incremental iterations.

The Profile

• The Hybrid Architect: 4–8 years of product experience or portfolio that proves you can build products that are as beautiful as they are functional.
• Multimodal Practitioner: You are proficient in the nuances of video, audio, and language models. You are comfortable "vibing" code and navigating a repository.
• Founder-Level Agency: You possess the "street-smart" intuition required to thrive in a high-growth environment. You are a self-starter who treats the product like your own company.
• Creator-Centric Soul: You likely have a background as an artist, designer, or filmmaker. You have a visceral empathy for the creative process and an obsession with empowering creators through technology.

Who You Are:

• 4-6 years of software engineering experience. You have a track record of shipping production software and take pride in clean, well-architected code.
• You are deeply hands-on with LLMs and generative AI. You know how to take a model beyond a prompt and into a reliable, scalable product feature. You understand RAG, prompt chaining, and model evaluation.
• You are driven by the "Doing Well by Doing Good" philosophy. You want to see your code solve real-world problems for real people, not just move numbers on a spreadsheet.
• You thrive in an office environment. You value the mentorship, speed, and social connection of a dedicated team. You want to be in the room where the big decisions happen.

Required

Requirements:

Know how to build APIs with Fast APIs
Knows how to code and debug
Clear understanding of the fundamentals of coding (Python)
Technical Problem solving ability
Must have shipped at least one Production app by yourself
Knows how to build UI in Angular / React using AI tools
Tech stack - Python, Fast APIs, AI, LLM, Azure, Angular, React

Key Responsibilities:

Assist in designing, developing, and implementing AI chatbots and virtual assistants using Python.
Work on natural language processing (NLP) tasks such as entity recognition, intent detection, and conversation flow.
Integrate AI models with existing cloud services and backend systems.
Test and optimize chatbot functionality to ensure performance, reliability, and user satisfaction.
Debug and troubleshoot technical issues related to AI systems.
Contribute to improving and scaling existing AI applications.
Stay updated on AI/ML trends, particularly in chatbot and AI assistant technologies.

* What you'll do

• Run rapid-cycle growth experiments across acquisition, activation, conversion, and retention.
• Own performance across outbound email, social channels, communities, partnerships, content, and demos.
• Build and optimize funnels - drive predictable pipeline and revenue growth.
• Partner with CEO, product, and our clients to inform GTM and shape product positioning.
• Define and monitor growth metrics (conversion %, CAC, win rate, churn).
• Conduct competitive research & identify new GTM opportunities.
• Work on creating playbooks that scale repeatable revenue processes.

*Who you are

• Interest in growth, marketing, or GTM (Fintech / SaaS preferred).
• Strong knowledge of Banking and Commercial lending
• Strong analytical mindset; fluent in data tools and experimentation.
• Comfortable executing hands-on: writing campaigns, building automations, running outbound.
• Entrepreneurial, resilient, action-oriented, and bias toward speed and results.
• Excellent communicator, skilled at selling complex value simply.
• Passion for AI & fintech transformation.
• Hungry to build category-defining products from 0→1.