Monitor autonomous AI agents in production, handle edge cases that exceed agent confidence thresholds, and approve high-stakes transactions. You are the last line of defense between agent decisions and real capital movement.

• 3+ years in trading operations or risk management
• Experience with automated trading systems and alerting
• Understanding of DeFi protocols and on-chain settlement
• Ability to make rapid decisions under time pressure
• Familiarity with AI model behavior and failure modes

Design agent trading strategies and fine-tune Tuatara vector embeddings. Translate market hypotheses into deployable agent configurations. Own the feedback loop between agent performance and model improvement.

• MS/PhD in ML, quantitative finance, or related field
• Production experience with LLM fine-tuning and RAG systems
• Strong Python; experience with vector databases and embeddings
• Track record in quantitative trading or systematic strategies
• Model-agnostic mindset — our moat is data, not any single model

Protect user funds and platform integrity across smart contracts, APIs, and AI agent operations. Conduct security audits, monitor for anomalous agent behavior, and respond to incidents across the full stack.

• 3+ years in application or blockchain security
• Smart contract auditing experience (Solidity, Foundry)
• Incident response and forensic analysis capabilities
• Understanding of AI agent attack surfaces and prompt injection
• Bug bounty track record or published security research

Build the proprietary Tuatara vector models that power our AI agents. Research novel embedding architectures for financial event prediction. Your models become the competitive moat that every agent on the platform depends on.

• PhD in mathematics, physics, CS, or quantitative finance
• Published research in representation learning or NLP
• Experience building production ML pipelines at scale
• Deep understanding of market microstructure and order flow
• Proficiency in PyTorch, JAX, or equivalent frameworks

Build and ship product features end-to-end using AI as your primary development tool. You think in systems, write specs that AI agents can execute, and own the full loop from user problem to deployed solution. Claude Code, Cursor, Copilot — these aren't nice-to-haves, they're your IDE.

• 2+ years shipping production software (any stack)
• Daily fluency with AI coding tools — you prompt, review, and iterate faster than you type
• Strong product instinct: you build what users need, not what's technically interesting
• Full-stack comfort: Python/FastAPI backend, vanilla JS/HTML frontend, PostgreSQL
• Bias toward action — you ship a working v1 before writing the spec for v2

Build AI-powered product features, integrations, and internal tools that bring our platform to life. You work across the stack to ship features that leverage LLMs, vector search, and real-time data pipelines — from prototype to production.

• 3+ years building production software (Python, JavaScript, or TypeScript)
• Hands-on experience integrating LLM APIs and ML model endpoints into products
• Full-stack capability: backend services, REST/WebSocket APIs, and frontend interfaces
• Experience shipping AI-powered features to real users at scale
• Comfort with rapid prototyping and iterating based on user feedback

Architect and scale the AI product infrastructure that powers EventTrader. Design ML pipelines, model serving systems, and data architectures that enable our AI agents to operate reliably at production scale with sub-second latency.

• 5+ years of software engineering with focus on backend systems
• Experience designing and operating distributed systems at scale
• Production ML pipeline experience: training, serving, monitoring, and retraining workflows
• Deep proficiency in Python, PostgreSQL, Redis, and containerized deployments
• Track record optimizing AI system performance: latency, throughput, cost efficiency

Design and operate autonomous QA pipelines where AI agents discover, reproduce, and validate bugs end-to-end. Build the infrastructure that enables zero-human-touch testing loops — from browser automation to regression detection to fix verification — so bugs are caught and resolved before they reach users.

• 3+ years in QA engineering, test automation, or CI/CD pipeline development
• Experience building autonomous testing systems using AI agents (browser automation, LLM-driven test generation)
• Strong Python and familiarity with Playwright, Selenium, or equivalent browser automation frameworks
• Understanding of agentic workflows: orchestrating multi-step AI pipelines with human-in-the-loop checkpoints
• Track record reducing manual QA burden through intelligent automation and self-healing test suites

Develop and optimize the Tuatara vector embedding algorithms that power EventTrader's predictive intelligence. Build feature-attributed vector intersection systems that uncover hidden relationships in financial data — not semantic similarity, but genuine structural relationships between entities, events, and market signals.

• MS/PhD in mathematics, computer science, or physics with focus on representation learning
• Deep experience with vector space models, embedding architectures, and dimensionality reduction techniques
• Published work or production systems in graph embeddings, knowledge graph completion, or relational learning
• Strong implementation skills in Python (NumPy, PyTorch/JAX) with attention to computational efficiency
• Interest in applying vector mathematics to financial signal extraction and hidden relationship discovery

Apply vector embedding and relationship extraction techniques to computational biology problems — signal transduction pathways, cell-cell communication networks, and molecular interaction modeling. Bridge the gap between bioinformatics and financial prediction by developing algorithms that detect hidden relationships in biological systems and translate those methods to market signals.

• PhD in computational biology, bioinformatics, systems biology, or related quantitative field
• Deep expertise in signal transduction modeling, cell-cell communication, or molecular network analysis
• Experience with graph neural networks, pathway analysis tools, or protein-protein interaction databases
• Strong Python and scientific computing stack (BioPython, NetworkX, SciPy, PyTorch)
• Interest in cross-domain application of biological network algorithms to financial relationship extraction

Build and operate data pipelines that ingest, process, and model satellite imagery and Earth Observation (EO) data for financial signal extraction. Transform raw geospatial data — SAR, multispectral, thermal — into proprietary features that give our AI agents an information edge no one else has.

• 3+ years in data engineering with experience in geospatial or satellite data pipelines
• Hands-on experience with EO platforms (Sentinel, Landsat, Planet, Maxar) and geospatial tooling (GDAL, Rasterio, GeoPandas)
• Strong Python and SQL; experience building ETL/ELT pipelines for large-scale imagery datasets
• Familiarity with proprietary data modeling — turning raw alternative data into structured, queryable features
• Interest in applying satellite intelligence to financial markets: supply chain monitoring, commodity tracking, economic activity estimation

Research and develop algorithms inspired by biological systems — swarm intelligence, evolutionary optimization, neural adaptation, and ecological dynamics — and apply them to financial markets and autonomous agent coordination. You bridge nature's 3.8 billion years of R&D with computational finance, extracting design principles from biological systems that outperform conventional approaches.

• PhD in biomimetics, biologically-inspired computing, evolutionary computation, or related field
• Research experience in swarm algorithms, genetic programming, ant colony optimization, or neural-inspired architectures
• Ability to translate biological mechanisms (homeostasis, stigmergy, predator-prey dynamics) into computational models
• Strong Python and scientific computing; experience implementing bio-inspired optimization at scale
• Published research or demonstrated interest in cross-domain application of biomimetic principles to finance, robotics, or multi-agent systems

Own the AI product roadmap from strategy to execution. Define what we build, why it matters, and how we measure success. You translate user needs and market signals into clear product specs, then work with engineering and AI agents to ship them.

• 4+ years product management experience, ideally in fintech, crypto, or AI-native products
• Shipped AI/ML-powered product features with measurable business impact
• Data-driven decision making: comfortable with SQL, analytics dashboards, and A/B testing
• Strong cross-functional leadership and stakeholder communication
• Technical depth: you can read code, understand system architecture, and speak the language of engineers