Define the technical direction and roadmap for applied AI and create AI agents to automate capabilities across the platform.
Architect and scale multi-agent orchestration workflows (e.g., LangGraph or equivalent), ensuring stateful, production-grade reliability.
Evaluation, Governance & Engineering Excellence
Design evaluation frameworks for agent behavior, decision quality, execution trajectories, and system performance, prioritizing reliability, transparency, and business relevance.
Champion engineering best practices: automated testing, observability, CI/CD, prompt and model evaluation, and production safeguards.
Establish responsible AI governance standards covering explainability, auditability, risk management, and regulatory compliance for a financial services context.
Stakeholder Engagement & Cross-Functional Impact
Partner with product, engineering, data, and business teams to identify high-value use cases and translate requirements into scalable AI-driven solutions.
Drive platform thinking with reusable agent patterns and shared capabilities that scale across domains, not bespoke one-offs.
Technical Qualifications
Programming & Engineering: Strong command of Python and modern software engineering including production design patterns, CI/CD, automated testing, and observability for AI-driven systems.
Agentic AI Systems: Demonstrated experience designing and deploying stateful, multi-step AI systems using agentic orchestration frameworks (e.g., LangGraph or equivalent).
NLP Foundations: Solid grasp of core NLP concepts - tokenization, embeddings, semantic search, and information retrieval techniques.
Data Science & Experimentation: Strong foundation in statistical modelling, data preprocessing, evaluation methodologies, and experimental design.
RAG & Retrieval Systems: Deep understanding of RAG architectures, retrieval pipeline optimisation, and vector database design.
ML Frameworks & Cloud Infrastructure: Hands-on experience with frameworks such as PyTorch or TensorFlow, and with cloud-native deployment environments including Kubernetes and containerisation.
Enterprise Integration: Experience designing AI systems that interface with enterprise backend platforms, APIs, and large-scale data pipelines.
Graph-Based Modelling: Familiarity with graph data structures and libraries (e.g., NetworkX, Neo4j) for modelling complex dependencies and relationships.
Requirements
Bachelor's or Master's degree in Computer Science, Data Science, Mathematics, AI/ML, or a related quantitative discipline.
10+ years of progressive experience building and shipping engineering, AI, or ML systems end-to-end in production, with recent hands-on work delivering LLM-based applications or agentic workflows.
3+ years leading engineering teams or large-scale cross-functional technical programmes, with a proven track record of driving delivery and organisational impact.
Demonstrated ability to manage complex technical programmes across multiple work streams, delivering high-quality outcomes at scale within Agile product and engineering environments.
Excellent written and verbal commu
Benefits
Vision insurance
Additional Information
About this role
About this role
We are building a next-generation, AI-native platform ecosystem for Alpha Generation that applies intelligent automation and agentic capabilities across investment technology and platform services, with a strong emphasis on reusable, platform-first capabilities over bespoke point solutions. This platform-first vision focuses on proactively monitoring, predicting, improving, and scaling engineering and operational workflows across core investment and technology pillars.
We are seeking a Vice President, AI Applied Engineer, a hands-on engineering leader who will shape and deliver this vision by driving AI‑first platform initiatives from concept through production at scale. This role will serve as a catalyst for adopting applied AI across the Alpha Generation platform organization, embedding modern engineering practices and accelerating platform maturity by enabling self-service, automation, and AI-powered workflows that reduce operational friction across teams. In this role, you will lead the design and delivery of a production‑grade and purpose‑built agentic AI capabilities.
This is an individual contributor leadership role , requiring deep technical ownership and strong influence. You will work closely with globally distributed engineering teams and partner with research, technology, and business leaders to drive platform‑wide development initiatives and foster an AI‑first mindset across the Alpha Generation ecosystem.
Blackrock · Mumbai, India