Responsibilities
- Design and develop production AI services that embed GenAI and ML into enterprise workflows.
- Build AI agents that can plan and execute multi-step tasks by calling approved tools/APIs, retrieving context, validating outputs, and safely handling failure cases.
- Implement retrieval-augmented generation (RAG) systems using vector search and hybrid retrieval to ground responses in enterprise data and documentation.
- Develop ML components where appropriate (e.g., classification, ranking, anomaly detection) and integrate them with LLM-based systems for hybrid intelligence.
- Establish robust evaluation and quality gates for agents and LLM systems (golden datasets, automated tests, regression suites, monitoring for drift/quality).
- Implement enterprise-grade governance: audit trails, provenance/citations, access control, privacy handling, and versioning (models/prompts/chains).
- Champion best practices for code quality, testing, automation, and performance/cost optimization.
- Mentor engineers to elevate technical craftsmanship, problem-solving, and design thinking.
- Collaborate cross-functionally to ensure technical solutions align with product goals and business outcomes.
- B.S./M.S. in Computer Science, Engineering, or related discipline.
- 8+ years of professional software engineering experience building and operating distributed systems in production.
- 3+ years delivering ML/AI systems to production with measurable outcomes and operational ownership.
- Demonstrable experience designing and building AI agents (agentic workflows) that: perform multi-step reasoning and task execution, use tools/functions/APIs, manage state appropriately, and include guardrails, validation, and safe fallback behavior.
- perform multi-step reasoning and task execution,
- use tools/functions/APIs,
- manage state appropriately,
- and include guardrails, validation, and safe fallback behavior.
- Strong knowledge of agentic design patterns, such as planning/execution loops, routing/specialist agents, retrieval + tool orchestration, verification/reflection, and human-in-the-loop approvals.
- Hands-on experience with LLM orchestration frameworks (e.g., LangChain or similar), including building reusable chains/agents and enforcing structured outputs.
- Hands-on experience with vector databases / retrieval systems (e.g., Pinecone, Weaviate, Milvus, pgvector, Elastic vector search, etc.) including indexing, chunking strategies, and hybrid search.
- Strong Python for AI/ML development and automation; strong backend experience in Java and/or TypeScript (APIs, services, integration patterns).
- Solid applied ML and evaluation fundamentals: dataset construction, precision/recall tradeoffs, calibration, and drift/quality monitoring.
- Enterprise mindset for security and controls: data minimization, auditability, traceability, access control, and operational resilience.
- Strong focus on clean architecture, maintainability, and production readiness.
- Excellent communication and leadership skills — able to guide teams and influence design direction.
Preferred qualifications
- Experience with Kubernetes, Docker, and cloud-native environments (AWS/GCP).
- Observability experience: OpenTelemetry, Prometheus/Grafana, and AI/LLM telemetry (quality metrics, latency, cost, tool-call traces).
- MLOps maturity: model registry, reproducibility, CI/CD for ML, feature stores, and governance workflows.
- Responsible AI experience: red-teaming, prompt injection defenses, content safety filters, privacy-preserving patterns.
- Familiarity with enterprise workflow/case management patterns and building AI into operational processes.
- Interest in financial systems, accounting, or investment technology.
About the company
At BlackRock, we are all connected by one mission: to help more and more people experience financial well-being. Our clients, and the people they serve, are saving for retirement, paying for their children’s educations, buying homes and starting businesses. Their investments also help to strengthen the global economy: support businesses small and large; finance infrastructure projects that connect and power cities; and facilitate innovations that drive progress.
This mission would not be possible without our smartest investment – the one we make in our employees. It’s why we’re dedicated to creating an environment where our colleagues feel welcomed, valued and supported with networks, benefits and development opportunities to help them thrive.
For additional information on BlackRock, please visit @blackrock | Twitter: @blackrock | LinkedIn: www.linkedin.com/company/blackrock
BlackRock is proud to be an equal opportunity workplace. We are committed to equal employment opportunity to all applicants and existing employees, and we evaluate qualified applicants without regard to race, creed, color, national origin, sex (including pregnancy and gender identity/expression), sexual orientation, age, ancestry, physical or mental disability, marital status, political affiliation, religion, citizenship status, genetic information, veteran status, or any other basis protected under applicable federal, state, or local law. View the EEOC’s Know Your Rights poster and its supplement and the pay transparency statement.
BlackRock is committed to full inclusion of all qualified individuals and to providing reasonable accommodations or job modifications for individuals with disabilities. If reasonable accommodation/adjustments are needed throughout the employment process, please email Disability.Assistance@blackrock.com. All requests are treated in line with our privacy policy.
BlackRock will consider for employment qualified applicants with arrest or conviction records in a manner consistent with the requirements of the law, including any applicable fair chance law.
Job Requisition #
R260733