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Magyarország
Hybrid
About this role
Senior AI Platform Engineer, VP / DIR
We are looking for a Senior AI Platform Engineer to help build and scale the firm's AI platform. This role sits at the intersection of artificial intelligence, software engineering, and platform architecture, with responsibility for delivering the shared services and frameworks that enable teams across the firm to build, evaluate, deploy, govern, and operate AI applications safely and efficiently.
You will work across foundational AI platform capabilities including agent runtimes and frameworks, evaluation systems, observability, guardrails, retrieval infrastructure, and governance controls. The role requires strong software engineering fundamentals, hands-on Python development, and the ability to turn rapidly evolving AI technologies into reliable, reusable, enterprise-grade platform services.
This is initially a senior individual contributor role with substantial technical leadership responsibilities. The role may expand into broader leadership over time, including mentoring, team formation, and potential people management.
Key Responsibilities
Design, build, and operate the firm’s AI platform: shared services, APIs, SDKs, and tooling that enable secure, consistent AI adoption.
Drive architecture across scalability, reliability, security, developer experience, and cost; define clear abstractions across application, framework, runtime, and infrastructure layers.
Build platform capabilities for LLM and agentic systems (orchestration, tool integration, memory, workflow execution, runtime management).
Develop retrieval and knowledge-access services supporting RAG and related patterns.
Implement evaluation frameworks to measure quality, reliability, safety, and business outcomes; use telemetry to prevent regressions and drive continuous improvement.
Build observability for tracing, metrics, logs, sessions, and execution history; deliver operational monitoring and diagnostics.
Implement guardrails for policy enforcement, risk mitigation, tenant isolation, and governance.
Write high-quality production code; establish strong engineering practices (testing, code review, CI/CD, documentation, operational ownership).
Operate reliable cloud-native services with monitoring, incident response, performance management, and capacity planning.
Lead complex technical initiatives end-to-end; mentor engineers and help shape platform standards and roadmaps. Potential people leadership as the team scales.
Required Qualifications
6+ years of software engineering experience with ownership of production services, platforms, or distributed systems.
Advanced proficiency in Python and strong software engineering fundamentals.
Deep knowledge of software architecture, service design, APIs, data modeling, concurrency, and distributed systems.
Experience building, deploying, and operating cloud-native services (Azure or similar).
Proficiency in testing strategies, CI/CD, observability, reliability engineering, and secure SDLC practices.
Proven track record leading ambiguous, cross-functional initiatives and delivering maintainable production systems.
Excellent written and verbal communication; able to explain architectural decisions to technical and non-technical stakeholders.
Preferred Qualifications (Strong Plus)
Hands-on experience building production AI or generative AI platforms and services.
Experience with LLMs, agent frameworks, tool use, orchestration, memory, and retrieval-augmented generation architectures.
Experience designing AI evaluation frameworks, benchmarks, regression testing, or quality measurement systems.
Experience building guardrails, responsible AI controls, governance capabilities, or safety and reliability mechanisms.
Experience with agent observability, distributed tracing, telemetry, and execution-history storage and retrieval.
Practical Rust experience, particularly for high-performance, reliable, or systems-oriented platform components.
Experience designing shared developer platforms, SDKs, or self-service capabilities used by multiple engineering teams.
Experience mentoring engineers, acting as a technical lead, or helping grow an engineering team.
Exposure to financial services or another regulated environment is beneficial but not required.
What Success Looks Like in This Role
Engineering teams can build and deploy AI solutions faster by using reliable, well-documented platform capabilities you help create.
Evaluation, observability, guardrail, and agent-runtime capabilities become reusable platform services adopted across multiple use cases.
The platform provides clear abstractions, production-grade reliability, and a strong developer experience without compromising governance requirements.
You become a recognised technical leader who shapes AI platform architecture, engineering standards, and delivery priorities. You help grow the team and can take on broader technical or people leadership responsibilities.
Additionally, employees are eligible for an annual discretionary bonus, and benefits including healthcare, leave benefits, and retirement benefits. BlackRock operates a pay-for-performance compensation philosophy and your total compensation may vary based on role, location, and firm, department and individual performance.
Our benefits
To help you stay energized, engaged and inspired, we offer a wide range of employee benefits including: retirement investment and tools designed to help you in building a sound financial future; access to education reimbursement; comprehensive resources to support your physical health and emotional well-being; family support programs; and Flexible Time Off (FTO) so you can relax, recharge and be there for the people you care about.
Our hybrid work model
BlackRock’s hybrid work model is designed to enable a culture of collaboration and apprenticeship that enriches the experience of our employees, while supporting flexibility for all. Employees are currently required to work at least 4 days in the office per week, with the flexibility to work from home 1 day a week. Some business groups may require more time in the office due to their roles and responsibilities. We remain focused on increasing the impactful moments that arise when we work together in person – aligned with our commitment to performance and innovation. As a new joiner, you can count on this hybrid model to accelerate your learning and onboarding experience here at BlackRock.
Guidance on AI use for candidates
At BlackRock, AI has long been part of how we work – enhancing decision-making, improving operations, and helping us deliver better outcomes for clients. We encourage candidates to use AI thoughtfully to learn, prepare, and work more effectively; but during our interview process, we want to focus on getting to know you through your own experiences, thinking, and judgment. To support you, we’ve provided guidance on when and how to use AI during our hiring process so you can approach each step with confidence and showcase your best self.
About BlackRock
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.
To learn more about BlackRock, please visit Careers.BlackRock.com. We also encourage you to get to know us on LinkedIn, Instagram, YouTube, X, and TikTok.
BlackRock is proud to be an Equal Opportunity Employer. We evaluate qualified applicants without regard to age, disability, race, religion, sex, sexual orientation and other protected characteristics at law.
