Careers
Join us in building the next generation of hedge fund technology.
Director of Data Engineering
Engineering•New York, NY•Full-time
Lead a global team to build next-generation data infrastructure that combines AI automation with production-grade reliability for the world's top hedge funds.
Requirements
- Bachelor’s or Master’s degree in Computer Science or a comparable discipline
- 7+ years in software/data engineering, with 2+ years in technical leadership or architecture roles
- Proven track record delivering complex, large-scale data platforms in production
- Hands-on experience building resilient data pipelines on Databricks using Delta Lake and Spark
- Exceptional programming skills in Python, Spark, and SQL
- Passion for AI—genuine excitement about how AI can transform data engineering
- Strong leadership skills with ability to mentor engineers and drive team execution
- Experience with financial analytics, hedge funds, or asset management strongly preferred
Responsibilities
- Lead the design and implementation of AI systems that automate pipeline creation and optimize data workflows
- Define and refine architecture for scalable, high-performance ETL pipelines and data platforms
- Manage and mentor a global team of data engineers across Bangalore and New York
- Work directly with hedge fund clients and stakeholders to gather requirements and deliver tailored solutions
- Build event-driven ETL architectures for real-time and batch processing needs
- Contribute to product strategy and roadmap based on market insights and client feedback
- Partner with product, backend, and frontend teams to ensure data integrity and performance
Applied AI Engineer
Engineering•New York, NY•Full-time
Build AI-powered, full-stack platforms for the world’s most sophisticated hedge funds — shipping production-grade applications that put agentic systems directly into the hands of investment teams.
Requirements
- Bachelor’s or Master’s degree in Computer Science or a comparable discipline
- 3+ years of full-stack experience with strong Python (FastAPI) and React
- Familiarity with and genuine interest in agentic systems — how LLMs, agentic tooling, and AI orchestration are reshaping software
- Experience with SQL, Polars/Pandas, OLAP databases, and cloud platforms (Azure/AWS/GCP)
- Deep curiosity about how hedge funds and asset managers think, invest, and use technology
- Excellent communicator comfortable working directly with non-technical users
- Strongly preferred: hands-on AI implementation experience (LLM APIs, MCP servers, LangGraph, RAG); financial data systems or portfolio analytics exposure
Responsibilities
- Build LLM-powered features like client-facing research intelligence tools, natural language query layers, and agentic workflows that fundamentally change how investment teams work
- Design and implement MCP-connected data sources and agentic pipelines using frameworks like Claude Code and LangGraph
- Build full-stack applications end-to-end — high-performance Python APIs and intuitive React frontends tailored to each client’s portfolio analytics and research workflows
- Develop and maintain ETL pipelines handling financial market data with reliability and performance
- Work directly with hedge fund teams to gather feedback, iterate fast, and deliver custom solutions in weeks, not months
Product Manager
Product•New York, NY•Full-time
Shape products at the intersection of AI and finance—working directly with hedge fund clients to build tools that transform institutional investing.
Requirements
- Bachelor’s or Master’s degree in Computer Science or a comparable discipline
- 8+ years of product management experience on consumer or enterprise software products with direct user exposure
- Proven track record building elegant solutions to complex problems, with shipped products users love
- Passion for AI—demonstrated experience using AI tools to streamline workflows and improve productivity
- Strong communication skills and ability to work with cross-functional, distributed teams
- User-centric mindset with passion for understanding customer needs
- 2+ years of software engineering experience strongly preferred
- Exposure to financial markets, hedge funds, or portfolio analytics highly valued
Responsibilities
- Experiment with and implement AI capabilities that enhance product functionality and automate workflows
- Own end-to-end product development, from gathering requirements to defining specifications and guiding implementation
- Work directly with hedge fund clients to understand their workflows, pain points, and requirements
- Transform complex financial and technical concepts into clear, actionable product specifications
- Collaborate with designers and engineers to build intuitive interfaces for sophisticated analytics
- Define product metrics, gather user feedback, and iterate based on real-world usage
- Balance technical feasibility, business value, and user needs across globally distributed teams
Applied AI Engineer
Engineering•Bangalore, IND•Full-time
Build AI-powered, full-stack platforms for the world’s most sophisticated hedge funds — shipping production-grade applications that put agentic systems directly into the hands of investment teams.
Requirements
- 3+ years of full-stack experience with strong Python (FastAPI) and React
- Familiarity with and genuine interest in agentic systems — how LLMs, agentic tooling, and AI orchestration are reshaping software
- Experience with SQL, Polars/Pandas, OLAP databases, and cloud platforms (Azure/AWS/GCP)
- Deep curiosity about how hedge funds and asset managers think, invest, and use technology
- Excellent communicator comfortable working directly with non-technical users
- Strongly preferred: hands-on AI implementation experience (LLM APIs, MCP servers, LangGraph, RAG); financial data systems or portfolio analytics exposure
Responsibilities
- Build LLM-powered features like client-facing research intelligence tools, natural language query layers, and agentic workflows that fundamentally change how investment teams work
- Design and implement MCP-connected data sources and agentic pipelines using frameworks like Claude Code and LangGraph
- Build full-stack applications end-to-end — high-performance Python APIs and intuitive React frontends tailored to each client’s portfolio analytics and research workflows
- Develop and maintain ETL pipelines handling financial market data with reliability and performance
- Work directly with hedge fund teams to gather feedback, iterate fast, and deliver custom solutions in weeks, not months
Cloud Engineer
Engineering•New York, NY•Full-time
Own the cloud infrastructure powering some of the world's most sophisticated hedge funds—from secure client environments and network architecture to backend systems and DevOps automation.
Requirements
- Bachelor’s or Master’s degree in Computer Science or a comparable discipline
- 3+ years of cloud infrastructure or platform engineering experience, preferably on Azure
- Proficiency in Infrastructure as Code (Terraform) and strong scripting skills (Bash, Python)
- Expertise in networking, VPNs, and secure cloud connectivity
- Hands-on experience with containerization (Docker) and CI/CD pipelines
- Deep understanding of database technologies for analytical and transactional workloads (Redis, MSSQL, Azure SQL)
- Excellent problem-solving and communication skills; comfort working in a fast-paced, client-facing environment
- Exposure to financial technology, hedge funds, or multi-tenant SaaS architecture strongly preferred
Responsibilities
- Design, implement, and manage scalable, secure cloud infrastructure (primarily Azure) using Infrastructure as Code (Terraform)
- Architect and manage VPN solutions, private endpoints, virtual networks, and client connectivity
- Build and maintain CI/CD pipelines, containerized environments (Docker), and automation scripts
- Provision and configure isolated single-tenant client environments, including onboarding and connectivity setup
- Design and optimize distributed backend systems—caching strategies, database selection, and OLAP/OLTP workflows
- Collaborate with Forward Deployed Engineers and the product team to align infrastructure decisions with client needs and business strategy
Technical Product Manager
Product•Bangalore, IND•Full-time
Own the full product and engineering lifecycle for a flagship client platform—from roadmap and sprint execution through QA and release—working at the intersection of product management, technical planning, and engineering coordination.
Requirements
- 8+ years in technical product management, engineering program management, or a combined engineering and product role
- Strong technical foundation with hands-on software or data engineering experience; able to reason credibly about architecture and engineering trade-offs
- Demonstrated ability to independently run agile delivery — sprint planning, backlog grooming, stand-ups, and retrospectives
- Experience writing PRDs and technical specifications for engineering teams
- Comfortable owning client and stakeholder relationships, including difficult conversations on scope and timelines
- Strongly preferred: experience with data platforms, financial technology, or capital markets; familiarity with Python, SQL, Databricks, or Azure; exposure to AI/ML product delivery
Responsibilities
- Own end-to-end sprint execution for the client engineering team — planning, stand-ups, backlog grooming, and retrospectives
- Translate requirements into detailed technical plans and architecture proposals; scope and break down roadmap decisions into executable sprint items
- Write PRDs for technical initiatives — regression testing frameworks, platform refactors, infrastructure upgrades, and feature enhancements
- Serve as the primary operational point of contact for the client, building toward full ownership of that relationship over time
- Own end-to-end QA and release management for all features and fixes going to UAT and production
- Coordinate AI implementation workflows as Hedgineer deploys new capabilities within client environments — managing priorities, timelines, and communication between clients and engineering
Forward Deployed Research Analyst — Long/Short Equity
Applied Finance•New York, NY•Full-time
Sit on-site with clients' investment teams, map how their workflows drive alpha, and use the Hedgineer platform to transform their processes with AI.
Requirements
- 3–6+ years in an equity research, fundamental research, or data science role
- Hands-on experience with Bloomberg, FactSet, Visible Alpha, Capital IQ, and other common datasets
- Active daily user of AI tools (real integration, not occasional experimentation)
- Comfortable with SQL and Python
- Strong presence with senior investment professionals; you build trust quickly and turn conversations into deliverables
- High ownership in an ambiguous environment — the playbook is being written in real time
Responsibilities
- Embed with PMs and research analysts to map their workflows and identify where AI creates the most leverage
- Build production-grade AI workflows — earnings previews, data vendor integrations, research synthesis — directly inside the client's platform
- Translate what you learn on the ground into skills, agents, and connectors with our engineering team
- Bring structured product feedback from the field as a daily platform power user
Forward Deployed Research Analyst — Long/Short Credit
Applied Finance•New York, NY•Full-time
Sit on-site with clients' investment teams, map exactly how their workflows drive alpha, and use the Hedgineer platform to transform those workflows with AI.
Requirements
- 3–6+ years in a fundamental or quantitative credit research role
- Hands-on experience with Bloomberg, BMS, FinDox, WSO, and other common data sources and platforms
- Active daily user of AI tools (real integration, not occasional experimentation)
- Comfortable with SQL and Python
- Strong presence with senior investment professionals; you build trust quickly and turn conversations into deliverables
- High ownership in an ambiguous environment — the playbook is being written in real time
Responsibilities
- Embed with PMs and credit analysts to understand current workflows and identify high-leverage automation opportunities
- Build production AI workflows — credit monitoring, issuer research, data vendor integrations — inside the client's environment
- Translate credit domain knowledge into skills, agents, and connectors with our engineering team
- Drive structured product feedback from the ground floor as a daily platform power user
- Codify what you learn into a reusable library of credit research playbooks for all clients
Forward Deployed IR Analyst
Applied Finance•New York, NY•Full-time
Embed with investor relations teams at sophisticated hedge funds, map their LP-facing workflows end-to-end, and use the Hedgineer platform to automate what's been manual for years — DDQs, performance reporting, capital activity, investor onboarding.
Requirements
- 3–6+ years in a core IR, capital raising, or fund marketing role at a hedge fund or asset manager
- Deep fluency in LP-facing workflows (DDQs, performance reporting, capital activity tracking, investor onboarding, and ongoing communications)
- Active daily user of AI tools with real opinions on where the leverage is and where it breaks
- Able to reason clearly about data, APIs, and how a skill or agent is constructed; you can scope complexity and translate domain logic for engineers
- Strong presence with senior investment professionals; you build trust quickly and turn conversations into deliverables
- High ownership in an ambiguous environment; the playbook is being written in real time
- Familiarity with CRMs like Backstop, Salesforce, or similar systems is a strong plus
Responsibilities
- Sit on-site with IR teams to understand LP-facing workflows and build AI workflows that transform them
- Automate high-friction IR processes — DDQ responses, performance report generation, investor onboarding, ongoing investor communications
- Translate IR workflows into skills, agents, and connectors in partnership with engineering
- Contribute structured product feedback as a daily platform power user
Forward Deployed Operations Analyst
Applied Finance•New York, NY•Full-time
Collaborate closely with clients' operations teams, map the manual workflows running the middle and back office, and build AI-powered replacements using the Hedgineer platform — trade reconciliation, cash management, treasury operations, prime brokerage reporting.
Requirements
- 3–6+ years in fund operations, middle office, or treasury at a hedge fund, prime broker, or fund administrator
- End-to-end fluency in fund ops workflows — trade booking, reconciliation, collateral management, treasury and cash management, NAV oversight, and prime brokerage relationships
- Active daily user of AI tools with genuine integration into how you work
- Comfortable reasoning about structured data, automation logic, and how an agent is constructed — ops is data-dense
- Strong presence with senior investment professionals; you build trust quickly and turn conversations into deliverables
- High ownership in an ambiguous environment; the playbook is being written in real time
- Familiarity with Geneva, Enfusion, Hazeltree, or similar systems is a strong plus
Responsibilities
- Embed with fund operations and treasury teams to map current workflows and identify automation opportunities
- Build production AI workflows across trade booking, reconciliation, cash management, and treasury operations
- Map how data moves between execution, prime, administrator, and internal systems — and redesign those flows with AI
- Translate operational domain knowledge into skills, agents, and connectors with our engineering team
Forward Deployed Risk Analyst
Applied Finance•New York, NY•Full-time
Embed within clients' risk teams, learn how they manage factor exposures, P&L attribution, and limit monitoring day-to-day, and use the Hedgineer platform to build AI workflows that change how risk operates.
Requirements
- 3–6+ years in portfolio risk, market risk, or quantitative risk management at a hedge fund or asset manager
- Deep fluency in factor risk models and how risk managers use those outputs day-to-day
- Active daily user of AI tools with genuine integration into how you work
- Comfortable working with position data, SQL, and Python; able to manipulate risk outputs and scope engineering work
- Strong client-facing presence with senior investment professionals
- Experience at a multi-PM or multi-strat fund is a strong plus
Responsibilities
- Sit on-site with risk managers to map daily workflows and identify where AI creates the most leverage
- Build production AI workflows across factor exposure reporting, P&L attribution, stress testing, and limit monitoring
- Translate risk domain knowledge into skills, agents, and connectors with our engineering team
- Drive structured product feedback as a daily platform power user