AI Engineer

About Finstock, Inc.

Finstock, Inc. builds AI-powered financial research, trading analytics, quantitative research, and market intelligence tools for experienced market users, analysts, research teams, and institutions.

Our AI systems support financial research workflows, market intelligence, retrieval, summarization, structured reasoning, user-scoped workspace features, analytics support, and responsible research-oriented decision-support experiences.

About the Role

We are hiring an AI Engineer to join Finstock's team on-site in Central, Hong Kong.

In this role, you will design, build, evaluate, and improve AI-powered product features for Finstock's financial research and market intelligence platform. You will work on retrieval-augmented generation, agentic workflows, prompt and tool orchestration, financial document understanding, model evaluation, search systems, and user-facing AI experiences.

You will collaborate closely with AI, engineering, data, product, quantitative research, and analyst teams to build reliable AI systems that are useful, secure, measurable, and aligned with responsible financial research standards.

This is an on-site role based in Central, Hong Kong. The role requires regular in-office collaboration with the team.

Key Responsibilities

• Design, build, test, and deploy AI-powered features for Finstock's financial research and market intelligence platform.
• Build retrieval-augmented generation systems, search workflows, financial document understanding features, agentic research flows, and AI-assisted analysis tools.
• Integrate large language models, embedding models, vector databases, search systems, APIs, and internal datasets into product workflows.
• Develop prompt orchestration, tool-calling workflows, structured output pipelines, evaluation harnesses, and model behavior tests.
• Build AI systems that can work with financial statements, market data, company disclosures, research notes, charts, transcripts, news, macro data, and user-scoped workspace context.
• Improve model reliability, grounding, latency, cost efficiency, observability, and production stability.
• Design safeguards to reduce hallucinations, unsupported claims, misleading outputs, poor retrieval quality, and inappropriate financial recommendations.
• Collaborate with Data Engineers to ensure AI systems use clean, permission-aware, well-documented, and reliable datasets.
• Collaborate with Software Engineers to integrate AI features into APIs, backend services, user interfaces, internal tools, and product workflows.
• Collaborate with Quantitative Researchers and Analysts to translate financial research requirements into practical AI workflows.
• Build internal evaluation datasets, test cases, quality rubrics, monitoring dashboards, and feedback loops for AI system performance.
• Support experimentation with model selection, fine-tuning, prompt engineering, retrieval strategies, ranking, reranking, summarization, classification, and financial reasoning workflows.
• Maintain documentation for AI architecture, model assumptions, evaluation methods, known limitations, safety boundaries, and operational procedures.
• Follow internal security, privacy, confidentiality, data licensing, and compliance requirements when working with financial and user-related data.

Required Qualifications

• 3+ years of professional experience in AI engineering, machine learning engineering, software engineering with AI systems, data science engineering, or a related technical role.
• Strong proficiency in Python.
• Experience building production or near-production AI, machine learning, LLM, NLP, retrieval, search, recommendation, or automation systems.
• Experience working with LLM APIs, open-source models, embeddings, vector databases, prompt engineering, tool calling, structured outputs, or agentic workflows.
• Experience with backend development, APIs, data pipelines, cloud infrastructure, or production software systems.
• Strong understanding of model evaluation, hallucination risk, retrieval quality, test design, latency, cost monitoring, and reliability tradeoffs.
• Familiarity with cloud platforms such as AWS, Google Cloud Platform, Microsoft Azure, or similar environments.
• Experience with Git, GitHub, CI/CD workflows, issue tracking, documentation, and collaborative engineering workflows.
• Strong debugging, analytical thinking, and problem-solving ability.
• Strong written communication skills and ability to explain technical decisions clearly to technical and non-technical stakeholders.
• Professional commitment to data security, confidentiality, and responsible handling of financial and user-related data.
• Ability to work on-site in Central, Hong Kong in compliance with applicable laws and eligibility requirements.

Preferred Qualifications

• Experience building AI systems for fintech, financial research, market intelligence, trading analytics, investment research platforms, SaaS products, or enterprise data products.
• Familiarity with financial data concepts such as equities, ETFs, indices, FX, crypto assets, commodities, financial statements, filings, transcripts, corporate actions, macro indicators, and market data APIs.
• Experience with frameworks or tools such as LangChain, LlamaIndex, OpenAI API, Anthropic API, Hugging Face, PyTorch, TensorFlow, scikit-learn, Ray, MLflow, or similar systems.
• Experience with vector databases and search systems such as Pinecone, Weaviate, Milvus, Chroma, pgvector, Elasticsearch, OpenSearch, or similar tools.
• Experience with backend frameworks such as FastAPI, Django, Flask, Node.js, NestJS, GraphQL, or similar systems.
• Experience with PostgreSQL, Redis, MongoDB, time-series databases, data warehouses, or lakehouse systems.
• Experience with Docker, Kubernetes, Terraform, GitHub Actions, observability tools, and production monitoring workflows.
• Experience designing model evaluation workflows, AI safety checks, guardrails, red-team tests, ranking systems, or human feedback loops.
• Experience with financial document parsing, table extraction, chart interpretation, time-series analysis, or numerical reasoning systems.
• Interest in financial research, market intelligence, quantitative analytics, and responsible AI for decision-support workflows.

What You Will Work On

You may work on projects such as:

• AI-powered financial research assistants and market intelligence workflows.
• Retrieval systems for financial documents, company data, research notes, market context, and user-scoped workspace data.
• Agentic workflows that help users structure research questions, retrieve relevant context, and produce grounded research outputs.
• Evaluation pipelines for hallucination detection, factuality, source grounding, financial reasoning quality, and response usefulness.
• AI features for summarizing filings, earnings updates, macro events, market news, company disclosures, and analyst notes.
• User-scoped workspace intelligence with secure data access and permission-aware retrieval.
• Internal tools that help analysts review, test, and improve AI-generated research outputs.
• Monitoring and observability systems for AI reliability, latency, cost, usage patterns, and quality metrics.
• Guardrails that help distinguish general financial research support from personalized investment advice.

What You Will Gain

• Opportunity to build AI systems for an AI-powered financial research and market intelligence platform.
• On-site collaboration with the team in Central, Hong Kong.
• Direct collaboration with AI, engineering, data, product, quantitative research, finance, operations, and regional analyst teams.
• Exposure to financial market data, research workflows, analytics systems, retrieval systems, and user-facing AI product development.
• A company email account and access to approved work tools, including Microsoft 365, Outlook, Teams, GitHub, cloud platforms, AI development tools, and company-approved productivity tools, subject to internal security and usage policies.
• Opportunity to participate in company offsite activities, subject to business schedule, travel eligibility, visa/documentation requirements, and company approval. Approved business-related travel, accommodation, and reasonable expenses will be covered by the company.

Important Role Boundaries

This is an AI engineering role supporting product systems, research workflows, model integration, retrieval systems, and responsible AI infrastructure.

The role does not require or permit the employee to:

• Provide personalized investment, legal, tax, accounting, or financial advice to users or clients.
• Recommend that any individual buy, sell, or hold a security based on personal circumstances.
• Execute trades or manage client funds.
• Handle client assets, deposits, or payments.
• Promise or imply investment returns, trading profits, or risk-free outcomes.
• Use unauthorized data sources, violate third-party data terms, or bypass licensing restrictions.
• Bypass internal security controls, access controls, audit requirements, or approved operational procedures.
• Deploy AI systems that intentionally mislead users, hide material limitations, or present unsupported claims as facts.
• Request applicants to pay any application fee, training fee, software fee, equipment fee, or onboarding fee.

Equal Opportunity Statement

Finstock, Inc. considers qualified applicants based on role-related skills, experience, technical ability, AI engineering ability, work quality, availability, and applicable engagement requirements. We do not make hiring decisions based on age, gender, gender identity, religion, ethnicity, race, national origin, disability, sexual orientation, marital status, family status, veteran status, or any other status protected by applicable law.