Founding team roles for an AI investment intelligence platform.

About the Role

We are seeking a Head of Quantitative Development to lead the development and productionization of QSentia's quantitative investment technology.

This person will sit at the intersection of quantitative research, machine learning, software engineering, portfolio construction, risk management, and execution.

You will be responsible not simply for developing agents, but for creating the infrastructure that turns research into robust investment systems capable of operating in institutional environments.

What You Will Own

• Lead QSentia's quantitative development organization.
• Own the research to production lifecycle for quantitative agents.
• Develop and productionize systematic strategies across equities, futures, digital assets, and multi asset portfolios.
• Advance QSentia's reinforcement learning architecture for portfolio allocation, position sizing, and adaptive risk management.
• Build institutional quality backtesting and simulation infrastructure.
• Implement walk forward testing and rigorous out of sample validation.
• Develop portfolio construction and optimization systems.
• Build volatility targeting, exposure management, drawdown controls, and risk budgeting frameworks.
• Develop transaction cost, slippage, liquidity, and market impact models.
• Build execution and order management logic.
• Design broker and exchange integrations.
• Establish standards for reproducible quantitative research.
• Prevent look ahead bias, survivorship bias, leakage, overfitting, and unrealistic execution assumptions.
• Develop agent performance attribution and monitoring.
• Work with engineering leadership to scale quantitative workloads across cloud infrastructure.
• Establish agent validation and production approval processes.
• Recruit and lead quantitative developers and researchers.

Ideal Background

• 10 or more years in quantitative finance, systematic trading, quantitative development, or financial engineering.
• Experience at a hedge fund, quantitative asset manager, proprietary trading firm, investment bank, market maker, or institutional trading organization.
• Exceptional Python skills.
• Strong understanding of quantitative portfolio management.
• Experience building production trading or investment systems.
• Deep understanding of statistics, probability, optimization, time series analysis, and financial markets.
• Experience with equities, futures, options, digital assets, or multi asset strategies.
• Strong understanding of portfolio construction, risk management, transaction costs, and execution.
• Experience with machine learning applied to financial markets.
• Strong software engineering practices and experience working with large financial datasets.

Highly Preferred

• Reinforcement learning experience.
• Deep learning and transformer experience.
• Experience with actor critic methods such as PPO, SAC, or TD3.
• Experience developing adaptive portfolio allocation or dynamic position sizing systems.
• Experience building long and short systematic portfolios.
• Knowledge of market microstructure.
• Experience with Interactive Brokers, Bloomberg, Polygon, Alpaca, CME, ICE, or institutional market data providers.
• AWS and distributed computing experience.
• Master's degree or PhD in Mathematics, Statistics, Computer Science, Physics, Engineering, Financial Engineering, Machine Learning, or a related quantitative discipline.

What Success Looks Like

You will transform QSentia's quantitative research into an institutional grade agent development and deployment engine.

Success means agents are not judged solely by backtest returns. They must demonstrate robust out of sample performance, controlled drawdowns, realistic transaction costs, explainable risk behavior, reproducibility, scalability, and readiness for deployment within professional investment environments.

Over time, you will build and lead the quantitative organization responsible for one of QSentia's most important competitive advantages: AI that learns not only where opportunities exist, but how much capital should be put at risk.

Compensation

This founding leadership role is initially equity based while QSentia completes its pre seed financing. Cash compensation will be introduced following financing, with compensation packages designed to be competitive for senior financial technology and quantitative talent.

About QSentia

QSentia is building an AI powered investment intelligence platform for family offices, RIAs, wealth managers, hedge funds, brokerages, and institutional investors.

Our platform combines proprietary reinforcement learning, adaptive portfolio risk management, explainable AI, agent observability, and institutional grade monitoring across equities, futures, digital assets, and multi asset strategies.

Unlike traditional investment platforms focused primarily on data or trading signals, QSentia is building the infrastructure professional investors need to evaluate, deploy, monitor, and govern AI driven investment agents.

Our long term vision is to become the trusted AI infrastructure powering the next generation of investment management.

About the Role

We are seeking a Head of Business Development to build QSentia's commercial organization from the ground up.

This is a founding leadership position for someone who understands how investment technology is sold into sophisticated financial institutions.

You will work directly with the Founder and CEO to convert our private beta into design partnerships, pilots, agent licensing agreements, SaaS subscriptions, and enterprise partnerships.

Your primary customers will include family offices, RIAs, wealth management firms, hedge funds, asset managers, brokerages, exchanges, and other financial institutions.

What You Will Own

• Develop and execute QSentia's institutional sales strategy.
• Build the company's sales pipeline from the ground up.
• Prospect and develop relationships with CIOs, portfolio managers, RIA owners, family office principals, heads of investments, and financial technology executives.
• Convert beta users and design partners into paying customers.
• Sell SaaS subscriptions, agent licenses, enterprise deployments, APIs, and white label solutions.
• Develop strategic partnerships with brokerages, custodians, exchanges, wealth platforms, and financial institutions.
• Lead product demonstrations and institutional sales presentations.
• Own the complete sales cycle from prospecting through negotiation and closing.
• Build pricing, packaging, sales collateral, CRM processes, and forecasting.
• Translate institutional customer feedback into actionable product requirements.
• Represent QSentia at investment management, wealth management, fintech, and quantitative finance conferences.
• Recruit and eventually lead QSentia's broader sales and business development organization.

Ideal Background

• 8 or more years of institutional financial services or fintech sales experience.
• Demonstrated success selling technology into investment management organizations.
• Existing relationships across family offices, RIAs, hedge funds, wealth managers, asset managers, or brokerages.
• Experience selling investment technology, market data, portfolio management software, quantitative research, trading infrastructure, or financial SaaS.
• Strong understanding of institutional investment workflows.
• Ability to communicate sophisticated AI and quantitative concepts to nontechnical decision makers.
• Experience closing enterprise contracts and navigating long institutional sales cycles.
• Entrepreneurial mindset and comfort building a commercial function from zero.
• Experience at companies such as Bloomberg, FactSet, BlackRock Aladdin, MSCI, Morningstar, S&P Global, Nasdaq, ICE, Broadridge, Envestnet, Addepar, or similar investment technology organizations.

What Success Looks Like

Your first objective will be turning QSentia's private beta into a repeatable commercial motion.

You will establish design partnerships, secure institutional pilots, close our first recurring customers, build strategic distribution relationships, and create the sales infrastructure required to scale QSentia from an early stage company into an institutional financial technology platform.

Compensation

This founding leadership role is initially equity based while QSentia completes its pre seed financing. Cash compensation will be introduced following financing.

A commission or revenue share component may be considered from day one to give senior institutional commercial leadership a direct economic incentive to bring QSentia its first paying customers while preserving cash.

About QSentia

QSentia is building an AI powered investment intelligence platform for family offices, RIAs, wealth managers, hedge funds, brokerages, and institutional investors.

Our platform combines proprietary reinforcement learning, adaptive portfolio risk management, explainable AI, agent observability, and institutional grade monitoring across equities, futures, digital assets, and multi asset strategies.

Unlike traditional investment platforms focused primarily on market data or trading signals, QSentia is building the infrastructure professional investors need to evaluate, deploy, monitor, and govern AI driven investment agents.

Our long term vision is to become the trusted AI infrastructure powering the next generation of investment management.

About the Role

We are seeking an experienced Senior Software Engineer to join QSentia's founding engineering team and help build the technology infrastructure behind our AI investment platform.

This is a highly technical, high ownership role for an engineer who enjoys building complex systems from the ground up.

You will work across backend services, APIs, financial data infrastructure, AI agent integration, broker connectivity, cloud infrastructure, security, and selected frontend capabilities.

Experience within financial services, fintech, capital markets, investment management, brokerage technology, or quantitative trading is strongly preferred.

You will work directly with the Founder, CTO, Head of Quantitative Development, quantitative researchers, and machine learning engineers.

What You Will Build

You will help develop the core technology that connects QSentia's quantitative agents to professional investment workflows, including agent deployment infrastructure, portfolio analytics, financial data pipelines, APIs, risk systems, monitoring, and eventually broker and execution integrations.

The objective is to transform sophisticated quantitative research into a secure, scalable, reliable product that institutional customers can use every day.

Key Responsibilities

• Design and build scalable backend services for QSentia's investment platform.
• Develop secure REST and event driven APIs for agents, portfolios, analytics, and external integrations.
• Build infrastructure for deploying and serving machine learning and reinforcement learning agents.
• Develop real time and batch financial data pipelines.
• Integrate market data from equities, futures, options, digital assets, news, and macroeconomic sources.
• Build integrations with brokerages, exchanges, custodians, and other financial technology providers.
• Develop portfolio, position, order, transaction, and account management services.
• Build agent telemetry, observability, logging, alerting, and audit infrastructure.
• Develop systems for portfolio risk monitoring and investment analytics.
• Build authentication, authorization, encryption, secrets management, and enterprise security controls.
• Design reliable databases and data models for financial and investment data.
• Build asynchronous and distributed processing systems for agent inference and financial workflows.
• Improve platform reliability, performance, scalability, and fault tolerance.
• Develop automated testing, CI and CD pipelines, deployment workflows, and infrastructure automation.
• Collaborate with quantitative researchers to productionize research code.
• Work with machine learning engineers to integrate AI agents into production applications.
• Participate in architecture decisions and technical roadmap development.
• Help establish QSentia's engineering standards and eventually mentor additional engineers.

Required Experience

• 7 or more years of professional software engineering experience.
• Advanced Python experience.
• Strong backend engineering experience.
• Experience designing production APIs and microservices.
• Strong knowledge of SQL and relational databases such as PostgreSQL.
• Experience with cloud infrastructure, preferably AWS.
• Experience with Docker and containerized applications.
• Strong understanding of distributed systems and asynchronous processing.
• Experience building secure production applications.
• Strong understanding of software architecture, testing, version control, and CI and CD.
• Ability to take ambiguous requirements and independently design production quality solutions.

Financial Experience Preferred

We strongly prefer candidates who have built technology within hedge funds, asset managers, investment banks, quantitative trading firms, proprietary trading firms, brokerages, exchanges, wealth management platforms, financial data providers, or fintech companies.

Experience building trading systems, portfolio management systems, order management systems, execution platforms, risk systems, financial data infrastructure, or investment analytics would be particularly valuable.

What We Offer

• Founding engineering team opportunity.
• Meaningful equity ownership.
• Direct influence over QSentia's technical architecture.
• Opportunity to build sophisticated AI and financial technology from the ground up.
• Work directly with quantitative researchers and AI engineers.
• High ownership and autonomy.
• Remote first environment.
• Opportunity to help build a category defining AI investment technology company.

Compensation

This position is initially equity based while QSentia completes its pre seed financing. Cash compensation will be introduced following financing and will be based on experience, responsibilities, and market benchmarks.

Closing

QSentia is building AI that professional investors can trust with real capital. We are looking for engineers who want to build the infrastructure that makes that possible.

About QSentia

QSentia is building an AI powered investment intelligence platform that helps family offices, wealth advisors, hedge funds, and institutional investors deploy institutional grade artificial intelligence through proprietary reinforcement learning, adaptive portfolio risk management, and explainable AI.

Our vision is to become the trusted AI infrastructure powering the future of investment management.

About the Role

We are seeking a founding Chief Technology Officer to lead the technical vision and execution of QSentia as we scale from private beta to institutional adoption.

You will own our engineering strategy, cloud architecture, platform scalability, security, and technical hiring while partnering closely with the Founder and CEO to build a category defining fintech company.

Responsibilities

• Define and execute the long term technology strategy.
• Build and lead a world class engineering organization.
• Design scalable cloud native infrastructure.
• Oversee backend, frontend, APIs, infrastructure, and platform security.
• Drive AI platform scalability, reliability, and observability.
• Build integrations with brokerages, custodians, and financial institutions.
• Recruit and mentor exceptional engineering talent.
• Represent QSentia with investors, partners, and enterprise customers.

Qualifications

• Ten or more years building enterprise software.
• Experience leading engineering organizations.
• Strong cloud architecture experience with AWS.
• Experience building financial technology, trading systems, or quantitative platforms.
• Experience with distributed systems, APIs, Kubernetes, Docker, and modern software architecture.
• Experience scaling SaaS products from early stage to production.
• Previous startup experience preferred.

Nice to Have

• Quantitative finance experience.
• AI or machine learning platform experience.
• Capital markets, brokerage, or institutional investing experience.

Compensation

This is an equity only role.

About the Role

We are looking for a founding Chief Data Officer to build one of the world's most advanced AI investment research organizations.

You will own the firm's data strategy, quantitative research, reinforcement learning development, feature engineering, alternative data, agent validation, and data governance.

Responsibilities

• Define the company's quantitative research roadmap.
• Lead development of reinforcement learning agents.
• Build institutional quality financial datasets.
• Develop alpha research across equities, futures, crypto, macro, and alternative data.
• Design feature engineering and agent validation pipelines.
• Build agent monitoring and performance analytics.
• Lead data governance and quality initiatives.
• Recruit quantitative researchers, machine learning scientists, and data engineers.

Qualifications

• Advanced degree in Computer Science, Machine Learning, Statistics, Mathematics, Finance, Engineering, or a related field.
• Ten or more years in quantitative research, machine learning, or financial data science.
• Experience with reinforcement learning, deep learning, time series modeling, and portfolio optimization.
• Strong Python, PyTorch, TensorFlow, SQL, and cloud computing experience.
• Experience working with institutional financial data.
• Strong understanding of equities, futures, options, and portfolio construction.

Nice to Have

• Previous hedge fund, asset management, quantitative trading, or proprietary trading experience.
• Experience building production AI systems.
• Publications or open source contributions in machine learning or quantitative finance.

What We Offer

• Founding executive opportunity.
• Significant equity ownership.
• Opportunity to shape the future of AI powered investment management.
• Direct influence on product strategy and company direction.
• Remote first environment.
• Opportunity to build a category defining fintech company from the ground up.

Closing

Join us in building the trusted AI infrastructure for investment management.