Top Tech Jobs & Startup Jobs in NYC, NY

Leads enterprise risk management strategy as a senior second-line risk leader. Responsibilities include developing strategic initiatives, overseeing research and analysis, advising business leaders, influencing enterprise decisions, managing projects and programs, communicating with executives, and mentoring teams. The role drives improved risk processes, customer experience, competitive differentiation, and collaboration across Capital One’s business and risk organizations.

Lead the architecture, development, deployment, optimization, governance, and observability of scalable AI platforms and systems. Build foundation model training, LLM inference, agentic workflows, similarity search, guardrails, and evaluation capabilities. Establish enterprise AI safety and transparency standards, drive long-term infrastructure strategy, mentor technical leaders, and guide organization-wide adoption of responsible AI solutions.

Build and operate scalable cloud data platforms, pipelines, and applications using Python, Spark, SQL, Databricks, Snowflake, and relational and NoSQL databases. Design data models, enforce engineering patterns and security standards, support distributed and streaming workloads, and deliver resilient solutions. Collaborate with product managers, software engineers, analysts, and data scientists while mentoring teammates and communicating technical concepts to stakeholders.

Develop the strategic direction for Capital One’s AI and machine learning platforms. Identify customer and business outcomes, define reusable platform capabilities, build strategy materials, solve cross-functional business problems, and support continuous delivery and improvement of AIML products. The role requires quantitative and qualitative analysis, stakeholder influence, senior leadership communication, people management, and project management.

Design, develop, deploy, and support foundational AI systems, including model training, LLM inference, agentic workflows, similarity search, guardrails, evaluation, governance, and observability. Optimize large-scale AI systems for cost, latency, throughput, scalability, and hardware utilization. Define reliability objectives, lead architecture and technical reviews, ensure security and compliance, contribute to long-term AI platform strategy, and mentor senior technical staff.

Develop and deploy advanced machine learning and data science solutions across large numeric and textual datasets. Partner with data scientists, engineers, and product managers to build customer-focused products. Lead model design, training, evaluation, validation, and implementation while researching emerging technologies and translating complex analyses into business outcomes.

Lead software engineering projects and developers building scalable full-stack systems with Scala, React, AWS, distributed microservices, and cloud technologies. Provide technical leadership across Agile teams, establish engineering standards, collaborate with product managers and architects, improve system performance, reduce technical debt, and influence technology strategy. Mentor engineers and support development of secure, reliable customer-facing financial products.

Design, develop, deploy, optimize, and support large-scale AI systems, including foundation models, LLM inference, agentic workflows, vector search, guardrails, evaluation, and orchestration pipelines. Lead cost-performance governance, technical design reviews, AI engineering standards, and long-term platform architecture. Apply state-of-the-art optimization techniques for latency, throughput, scalability, hardware utilization, and inference costs while mentoring senior technical staff and ensuring responsible AI practices.

Build and lead development of Capital One Travel’s unified checkout and My Trips platform. Design scalable full-stack applications, distributed microservices, APIs, cloud-based solutions, and reusable frameworks using modern languages and AWS technologies. Provide technical leadership across Agile teams, establish engineering standards, mentor developers, improve performance, reduce technical debt, and influence long-term technology strategy.

Design, develop, deploy, and support foundational AI systems, including foundation model training, LLM inference, agentic workflows, similarity search, guardrails, evaluation, governance, and observability. Optimize AI systems for scalability, cost, latency, throughput, and hardware utilization. Own complex architectures, define reliability objectives, lead technical reviews, collaborate across engineering and product teams, and mentor senior technical staff.