Are you interested in building innovative technology that shapes the financial markets? Do you like working at the speed of a startup, and tackling some of the worlds most interesting challenges? Do you want to work with, and learn from, hands-on leaders in technology and finance?
At BlackRock, we are looking for Software Engineers who like to innovate and solve sophisticated problems. We recognize that strength comes from diversity, and will embrace your outstanding skills, curiosity, and passion while giving you the opportunity to grow technically and as an individual.
We invest and protect over $11 trillion (USD) in assets and have an extraordinary responsibility to our clients all over the world. Our technology empowers millions of investors to save for retirement, pay for college, buy a home and improve their financial well-being.
Being a technologist at BlackRock means you get the best of both worlds: working for one of the most sophisticated financial companies and being part of a software development team responsible for next generation technology and solutions.
Team Overview:
The Aladdin Engineering Post Trade & Accounting Team provides technology solutions for BlackRocks post trade investment life cycle operational processes including Accounting & Reporting platform to support the scale at which BlackRock operates. The team is responsible for a suite of applications including highly complex and scalable performance calculation engines, investment accounting, client reporting systems, platform for reconciliation, and derivative management. We innovate incrementally and focus on high level of client service through responsiveness, accuracy, and efficiency.
Responsibilities:
• AI-Accelerated Design & Development: Design, develop, deliver, and maintain web applications across frontend and backend, leveraging AI-powered development tools (e.g., code generation, intelligent code completion, automated refactoring) to dramatically accelerate solutioning and product build cycles while maintaining consistent, high-quality output.
• Agentic Workflow Engineering: Architect, build, and operationalize agentic AI workflows—including multi-agent orchestration, tool-use patterns, and autonomous task execution pipelines—to automate complex business processes and augment engineering productivity.
• Technical Leadership with AI Fluency: Demonstrate technical leadership of software design & architecture, incorporating AI-assisted development practices into the strategic product roadmap and establishing team-wide standards for responsible AI tool adoption.
• Delivery & Planning: Deliver plans and define milestones, prioritize initiatives, and properly allocate resources—using AI tooling to improve estimation accuracy and accelerate delivery against business commitments.
• Cross-Functional Collaboration: Collaborate with cross-functional teams in a multi-office, multi-country environment to define, design, and ship high-quality software solutions. Champion AI-augmented development practices across teams.
• Frontend & Backend Integration: Implement responsive user interface applications using Angular and ensure seamless integration with backend services through an API-first approach, using AI-assisted coding tools to maintain velocity and code quality.
• Complex Problem Solving: Design and develop innovative solutions to complex problems, using AI reasoning tools and agentic patterns to identify issues, explore solution spaces faster, and eliminate roadblocks.
• SDLC Participation: Work with project managers, technical leads, and business analysts to contribute throughout the SDLC cycle, integrating AI-assisted testing, code review, and documentation generation into standard workflows.
• Stakeholder Management: Manage stakeholders for driving business decisions, negotiating priorities, and partner with various business teams to drive strategy and technology adoption—including communicating the value and limitations of AI-augmented development.
• Quality & Resilience: Ensure scale, resilience, and stability through risk identification and mitigation, AI-assisted code reviews, creation of robust test suites (including AI-generated test cases), and providing level two support.
• Continuous Improvement & Innovation: Foster continuous improvement in software development practices through AI-driven innovation and automation. Evaluate and integrate emerging AI development tools, LLM-based agents, and intelligent automation frameworks into team workflows.
• Staying Current: Stay up to date with rapidly evolving AI/ML tooling, agentic frameworks (e.g., LangChain, LangGraph, Google ADK, AutoGen, CrewAI), and industry trends to continuously improve development processes and maintain a competitive edge.
Skills & Experience:
• Core Programming: Hands-on programming experience in Java, Python, JavaScript, and TypeScript with strong OO skills and design patterns.
• AI-Assisted Development: Demonstrated experience using AI-powered development tools (e.g., GitHub Copilot, Cursor, Windsurf, ChatGPT, Claude) to accelerate coding, debugging, testing, and documentation—with a track record of maintaining high code quality at increased velocity.
• Agentic AI & Workflow Automation: Practical experience building agentic workflows using frameworks such as LangChain, LangGraph, Google ADK, AutoGen, or CrewAI—including multi-agent orchestration, tool integration, retrieval-augmented generation (RAG), and autonomous task execution.
• LLM Integration: Experience integrating large language models into applications via APIs (OpenAI, Azure OpenAI, Anthropic, Google Vertex AI) and understanding of prompt engineering, function calling, and context management.
• Frontend Frameworks: Experience with Angular, TypeScript, and responsive web design (Webpack, HTML5, CSS3).
• Backend & Open Source Stacks: Experience with Spring, Tomcat, Maven, JUnit, NodeJS, and Express.
• Databases: Experience working with relational (Sybase) and NoSQL databases.
• Architecture & Problem Solving: Strong problem-solving, analytical, and software architecture skills—with the ability to evaluate where AI tooling adds genuine value vs. where traditional approaches are more appropriate.
• Collaboration: Experience partnering with other teams, sponsors, and user groups who are on the same product journey, including evangelizing AI-augmented practices.
• Agile Practices: Ability to work in Agile/Scrum development environments with strong teamwork, communication, and time management skills.
• Innovation Mindset: Thought leader around AI-driven development, new/cutting-edge technologies, and their practical application in enterprise software.
Distributed Systems Engineering:
• Strong experience designing and operating distributed systems, including:
• Service oriented and microservices architectures
• Event driven and asynchronous processing
• Failure handling, retries, idempotency, and resilience
• Performance tuning and scalability under load
Qualifications:
• B.S. / M.S. degree in Computer Science, Engineering, or related subject area
• 7+ years of hands-on development experience
• 1+ years of demonstrable experience using AI-assisted development tools in production workflows
• Experience building or contributing to at least one agentic AI system or multi-agent workflow
Nice to Have:
• Experience with cloud native tools and cloud platforms (Azure, AWS, or GCP)
• Exposure to high-scale distributed technologies
• Experience with DevOps, CI/CD pipelines, and tools like Azure DevOps—including AI-augmented CI/CD practices
• Experience with MCP (Model Context Protocol), A2A (Agent-to-Agent) protocols, or similar agent communication standards
• Experience or real interest in finance, investment processes, and/or an ability to translate business problems into technical and AI-powered solutions
• Familiarity with AI safety, responsible AI practices, and governance frameworks for AI tool usage in enterprise environments