artificial intelligence engineer

C2R Ventures

<div>
 
 Elite multi-strategy hedge fund manager that invests globally in a wide array of assets and strategies, is seeking an elite Agentic AI Research Engineer to play a key role in the ongoing development and enhancement of their investment process.
 
 
 
 
 
 Do not need financial experience to apply, but of course it is welcome. Candidates from AI research arms/divisions of notable bigtech companies and/or AI start-ups with elite VC backing are very welcome to apply.
 
 
 
 
 
 This Engineer will be embedded in investment teams to augment their investment process through designing and building multi-agent frameworks by developing deep understanding of each business and leveraging cutting-edge methods.
 
 
 
 
 
 This is a Full Stack role that will encompass the building of foundational infrastructure and developing robust data pipelines through agentic design.
 
 
 
 
 
 
 Responsibilities:
 
 
 <ul>
 <li>
 Work with investment teams to find solutions to their most vexing challenges, applying agents to assist in solving problems
 </li>
 <li>
 Design, build, and integrate a multi-agent AI framework that can orchestrate deep research in and across vastly different subject matter and domain expertise
 </li>
 <li>
 Implement rigorous quantitative benchmarks for large scale agentic tasks
 </li>
 <li>
 Assist with automated evaluation of AI models and prompts across a wide variety of project and investment teams
 </li>
 <li>
 Help create and optimize data mixes for model training that maximize agent performance or ease of use on agentic tasks
 </li>
 </ul>
 
 
 
 
 
 Requirements:
 
 
 <ul>
 <li>
 0&gt;1 builder who is comfortable with uncertainty, operates with high agency, and excels at rapid iteration and shipping
 </li>
 <li>
 Experience developing complex agentic systems using LLMs with an emphasis on agentic harness design (e.g., communication architectures for agents)
 </li>
 <li>
 Successfully demonstrated the ability of taking a product from conception to completion
 </li>
 <li>
 Understanding of LLM-as-judge, reward hacking, specification gaming robustness problems
 </li>
 <li>
 Have strong Python skills and can build robust infrastructure across the stack
 </li>
 </ul>
</div>

Artificial Intelligence Engineer

James Search Group

<div>
 
 
 AI/ML Engineer
 
 
 
 
 Location:
 
 New York, NY
 
 
 
 Compensation:
 
 $135,000 &ndash; $175,000 base + bonus + full benefits, (401(k), and more)
 
 
 
 Industry:
 
 Global P&amp;C Insurance
 
 
 
 
 
 
 About the role and the company.
 
 
 
 James Search Group is working closely with a top-tier global property &amp; casualty insurance carrier to identify an
 
 AI/ML Engineer
 
 to join their enterprise Data and Artificial Intelligence division. This team is driving innovation across the business by developing and scaling AI capabilities that unlock new value and improve decision-making across underwriting, claims, and customer engagement.
 
 
 
 
 
 As an AI/ML Engineer, you'll collaborate with senior team members to build, refine, and deploy predictive models and intelligent systems. The ideal candidate is skilled in analytics, curious by nature, and passionate about transforming complex data into practical solutions that deliver measurable business impact.
 
 
 
 
 
 
 Key Responsibilities:
 
 
 <ul>
 <li>
 Support the development and deployment of AI/ML models&mdash;including classification, forecasting, uplift and propensity modeling, and foundational model tuning.
 </li>
 <li>
 Collaborate with cross-functional teams to identify use cases where data science can enhance operational efficiency and business performance.
 </li>
 <li>
 Partner with business, IT, and strategy teams to ensure AI models are scalable, impactful, and aligned with organizational goals.
 </li>
 <li>
 Communicate analytical findings clearly to stakeholders with varying levels of technical knowledge.
 </li>
 </ul>
 
 
 
 
 
 Required Qualifications:
 
 
 <ul>
 <li>
 Master&rsquo;s degree in Data Science, Statistics, Mathematics, Computer Science, or a related quantitative discipline; Ph.D. a plus.
 </li>
 <li>
 Minimum of 2 years&rsquo; experience applying advanced analytics methods (e.g., decision trees, logistic regression, neural networks, random forests).
 </li>
 <li>
 Proficiency in R or Python for analytics and model development, including work with both structured and unstructured data.
 </li>
 <li>
 Proven ability to manage and integrate large, complex datasets and an understanding of end-to-end data modeling processes.
 </li>
 <li>
 Strong written and verbal communication skills with the ability to connect technical outputs to business strategy.
 </li>
 </ul>
 
 
 
 
 
 Preferred Qualifications:
 
 
 <ul>
 <li>
 Internship or project experience in machine learning, AI engineering, or related roles&mdash;especially in insurance or financial services.
 </li>
 <li>
 Familiarity with actuarial concepts or insurance-specific data models.
 </li>
 <li>
 Enthusiastic about continued learning in AI/ML and staying current with new tools and methodologies.
 </li>
 <li>
 Comfortable in a collaborative, fast-paced, and agile working environment.
 </li>
 </ul>
 
 
 
 
 This is a unique opportunity to grow your career with a highly respected organization investing in next-generation analytics.
 
 
 
 
 
 
 Apply today
 
 to help reshape the future of insurance through data and AI innovation.
 
</div>

Machine Learning Engineer

ReadMe

<div>
 
 📍 Locations: San Francisco (Hybrid), New York (Hybrid), Columbus (Hybrid), or Remote (US)
 
 
 
 We&rsquo;re hiring an AI Engineer to shape how AI shows up across ReadMe&rsquo;s product: from how developers explore and understand APIs to how companies author and maintain their documentation.
 
 
 We&rsquo;re at the forefront of a major shift in developer experience:
 
 
 <ul>
 <li>
 AI agents need APIs to talk to each other, and those APIs need to be understandable, structured, and explorable
 </li>
 <li>
 At the same time, writers and developers are looking for better ways to generate and maintain documentation with AI
 
 
 </li>
 </ul>
 We're a small team of humans (and one owl) working together to do big things &mdash; and that&rsquo;s where you come in. In this role you&rsquo;ll have a transformational impact on ReadMe across both the trajectory of the business and our thriving culture.
 
 
 🦉 What we do
 
 
 ReadMe helps more than 5,000 leading startups and tech companies build beautiful, personalized, and interactive developer hubs. If you&rsquo;ve ever visited the developer docs for PagerDuty, Samsara, or Nvidia, you&rsquo;ve used ReadMe!
 
 
 We love what we do because it&rsquo;s so much more than just documentation. We&rsquo;re providing tools for teams to build a better developer experience and make their products and APIs easier to use. We&rsquo;ve got great support from our investors at Accel who led our Series A, and our interview process reflects the open, caring, and whimsical culture we want to maintain as we scale.
 
 
 ✅ What you&rsquo;ll do here
 
 
 This isn&rsquo;t a feature team where a PM hands you tickets. You&rsquo;ll help decide what gets built, why it matters, and how it works end-to-end. You&rsquo;ll work on systems that are already live across thousands of developer hubs and define what they become next.
 
 
 ReadMe's AI surface spans three bets we're doubling down on:
 
 
 <ul>
 <li>
 Documentation that writes itself. AI that watches code change and keeps docs current &mdash; from PR-level suggestions to org-wide audits that surface and fix quality issues at scale.
 </li>
 <li>
 Answers, not search results. A conversational layer embedded directly in developer hubs, grounded in real docs, that gives developers the right answer instead of a list of links to dig through.
 </li>
 <li>
 APIs that are agent-ready. As AI agents increasingly talk to APIs, the structure and clarity of those specs matters more than ever. We're building the systems that make APIs understandable by both humans and machines.
 
 
 </li>
 </ul>
 Day to day, you&rsquo;ll:
 
 
 <ul>
 <li>
 Design end-to-end AI systems: combining LLMs, embeddings, retrieval pipelines, and structured outputs into reliable product features.
 </li>
 <li>
 Build grounding and retrieval layers: indexing docs, OpenAPI specs, and customer data to support accurate, context-aware generation.
 </li>
 <li>
 Define evaluation systems: measuring accuracy, latency, cost, and user impact; building feedback loops to continuously improve quality.
 </li>
 <li>
 Handle real-world complexity: malformed specs, inconsistent docs, edge-case APIs, and ambiguous user queries.
 </li>
 <li>
 Make architectural tradeoffs: latency vs. quality, cost vs. coverage, deterministic vs. generative approaches.
 </li>
 <li>
 Own production reliability: observability, fallbacks, rate limiting, and safe degradation when systems fail.
 </li>
 <li>
 Work across the stack: from model orchestration and backend systems to the UI surfaces that expose them.
 
 
 </li>
 </ul>
 💙 You'll love this job if you...
 
 
 <ul>
 <li>
 Want to own meaningful systems end-to-end, not just features.
 </li>
 <li>
 Care deeply about developer experience and documentation quality.
 </li>
 <li>
 Enjoy working on problems where AI, APIs, and product design intersect.
 </li>
 <li>
 Have strong instincts about what makes AI actually useful and where the industry is headed.
 
 
 </li>
 </ul>
 ️ ⭐️ This role is a great fit if you have...
 
 
 <ul>
 <li>
 Experience building with LLMs in production, not just prototypes.
 </li>
 <li>
 Strong JavaScript/TypeScript or Python experience.
 </li>
 <li>
 Experience working with:
 </li>
 <ul>
 <li>
 Embeddings and retrieval systems (RAG).
 </li>
 <li>
 Prompting and structured outputs.
 </li>
 <li>
 Evaluation and iteration of AI systems (quality, latency, cost).
 </li>
 </ul>
 <li>
 Comfort working with APIs and structured data (JSON, OpenAPI, schemas).
 </li>
 <li>
 Experience designing and shipping end-to-end systems, from backend pipelines to user-facing product surfaces.
 </li>
 <li>
 Strong instincts around when to use AI vs. deterministic approaches.
 </li>
 <li>
 Experience improving AI reliability, observability, and production readiness.
 </li>
 <li>
 Familiarity with real-world edge cases (messy data, inconsistent inputs, ambiguous queries) and how to handle them.
 
 
 </li>
 </ul>
 🌱 How you'll grow within one month...
 
 
 <ul>
 <li>
 Build a deep understanding of ReadMe&rsquo;s AI systems and product surfaces.
 </li>
 <li>
 Ship meaningful improvements to existing AI features.
 </li>
 <li>
 Get close to real customer workflows and pain points.
 
 
 </li>
 </ul>
 🪴 Within a few months, you'll...
 
 
 <ul>
 <li>
 Own a core part of one of our AI systems.
 </li>
 <li>
 Drive improvements in quality, reliability, and user experience.
 </li>
 <li>
 Contribute to product and technical direction.
 
 
 </li>
 </ul>
 🌳 Within your first year, you'll...
 
 
 <ul>
 <li>
 Be a key driver of AI across the product.
 </li>
 <li>
 Ship systems used daily by thousands of developers and teams.
 </li>
 <li>
 Help define how AI reshapes developer hubs and API workflows.
 
 
 </li>
 </ul>
 🛣️ What's the hiring process like?
 
 
 <ul>
 <li>
 We can&rsquo;t wait to read your resume and (hopefully personality-filled) cover letter! Let us know what excites you about full stack engineering, and help us get to know you better!
 </li>
 <li>
 If we think we might be a good fit for you, we&rsquo;ll set up a 30 minute phone chat with our VP Engineering Moses! He&rsquo;ll tell you more about the role, and get a chance to hear about your experiences.
 </li>
 <li>
 Next will be a second 30 minute phone interview with Davin, one of our Engineering Managers, where we&rsquo;ll dive a bit more into your background.
 </li>
 <li>
 We&rsquo;ll then do a technical assessment with a couple of ReadMe engineers.
 </li>
 <li>
 Finally we&rsquo;ll invite you to an "onsite" interview conducted over Zoom! These usually take 3.5 to 5 hours including an hour break in between. We are able to be flexible with the schedule and split it up over two days if that works best for you! We start with a 15-minute get-to-know-you with the people you&rsquo;ll be interviewing with, and then have you talk with people one-on-one later on.
 </li>
 <li>
 We&rsquo;ll let you know how things went within a week! If it still seems like a good fit all around, we&rsquo;ll extend you an offer! If not, we will update you to let you know so you aren&rsquo;t left hanging.
 
 
 </li>
 </ul>
 
 ✨ Our Benefits Include&hellip;
 
 
 
 <ul>
 <li>
 Unlimited PTO with a three-week minimum. 🏝️
 </li>
 <li>
 Fully covered medical, dental, and vision insurance for you, and 100% for your dependents.
 </li>
 <li>
 A One Medical membership. 👨&zwj;⚕️
 </li>
 <li>
 A gym or fitness stipend of up to $150 per month. 🏋️&zwj;&female;️
 </li>
 <li>
 One-to-one donation matching of up to $1,000 per year. 💸
 </li>
 <li>
 Twelve weeks of paid parental leave after the birth or adoption of a child. 🐣
 </li>
 <li>
 Work from home. 🏠
 </li>
 <li>
 Three offsite retreats per year to get together with coworkers and plan for the quarter ahead. ✈️
 </li>
 <li>
 Take a look at our handbook for more information on our benefits! 📘
 
 
 </li>
 </ul>
 Not sure if you&rsquo;d be the right fit? Apply anyway! We&rsquo;d love to see your application.
 
 
 
 At ReadMe, we&rsquo;re committed to cultivating a diverse and inclusive workplace. We welcome people of all different backgrounds, experiences, abilities, and perspectives. We are an equal opportunity employer and a pleasant and supportive place to work. We'd love to have you come join us here! ReadMe is open to hiring folks fully remote in the US, hybrid, or in-person at our New York or San Francisco HQ.
 
 
 
</div>

AI Engineer

Research Scientist Intern, AI Alignment

Cooley LLP

<div>Cooley is seeking an Artificial Intelligence (&ldquo;AI&rdquo;) Solutions Engineer to join the Practice Engineering team within the Innovation department.
Position summary: As the leading technology law firm, Cooley is determined to become a leader in the digital practice of law. Cooley Innovation embraces a culture of customer service excellence, and all members of the department are expected to move this agenda forward. To that end, under the direction of the Manager of Product Engineering, and collaborating directly with practitioners, technical teams, and innovation stakeholders, the Artificial Intelligence (&ldquo;AI&rdquo;) Solutions Engineer leads process automation initiatives by driving prototype-based discovery and building functional workflow demonstrations that validate repeatable, end-to-end processes&mdash;from defined inputs through tool orchestration to outputs that meet specified acceptance criteria. This includes developing multi-step automations that combine deterministic scripting with AI workflows, including advanced prompting, retrieval-augmented generation (RAG), and agentic techniques. This role partners across multiple domains including Practice Innovation, Knowledge Management, Software Engineering, as well as resource attorneys and other practitioners across a range of offices and practice areas. Specific duties and responsibilities include, but are not limited to, the following:
Position responsibilities:<ul><li>
Responsible for the management, design and development and testing of legal workflow automations, form-building solutions and expert knowledge systems</li><li>
Elicit attorney/practitioner requirements, map end-to-end process steps, define decision points and failure modes, and produce clear acceptance criteria and test cases that make the workflow measurable and reviewable</li><li>
Rapidly build and iterate working proofs-of-concept that validate feasibility of repeatable processes, combining deterministic logic (rules/scripting) with AI steps (prompting, retrieval, tool-use/agents) to produce usable outputs aligned to acceptance criteria</li><li>
Working with Knowledge Management and practitioners, create/maintain the workflow&rsquo;s &ldquo;source of truth&rdquo; (playbooks, templates, matter-type guidance, clause libraries, FAQs), implement retrieval strategies and citation/traceability expectations, and partner with attorneys to ensure substantive content accuracy and ongoing governance of knowledge updates</li><li>
Evaluate AI and technology components; design measurable validation workflows (including Python-based integrations) to test use cases, assess feasibility, and generate stakeholder-ready findings</li><li>
Build RPA workflows and API integrations to measure and report adoption and performance; deliver executive-facing analytics that enable leadership advocacy and decision-making</li><li>
Design and maintain knowledge applications, including working with Knowledge Management and attorneys to ensure substantive legal content is accurate</li><li>
Coordinate training, support, documentation and resource material in support of processes and systems</li><li>
Engage with end-users to gather feedback, observe and map routines and processes</li><li>
Create and maintain project planning documentation, including business end-user requirements, user and administrative workflows and quality assurance procedures</li><li>
All other duties as assigned or required</li></ul>
Skills and experience:
Required:<ul><li>
After orientation at Cooley LLP, exhibit proficiency in the Microsoft Office suite, iManage and other firm applications</li><li>
Ability to work extended and/or weekend hours, as required</li><li>
Ability to travel, as required</li><li>
3+ years direct applicable experience (e.g., delivery of GenAI-powered workflows and solutions)</li><li>
Experience with API-driven integrations, workflow automations, document automation (e.g. excel and docx), and generative AI</li><li>
Experience working with MCP servers and building agentic workflows using MCP and non-MCP tools</li><li>
Experience designing and implementing retrieval-grounded generation in permissioned environments</li><li>
Proficiency extracting from and creating common enterprise file formats like docx, pptx, xlsx, pdf, etc.</li></ul>
Preferred:<ul><li>
Bachelor&rsquo;s degree</li><li>
Working knowledge of business analysis, knowledge management, information systems or other-related field</li><li>
Experience working in professional services, or a legal services environment with preference to experience in AMLAW 200 law firm or in-house legal department with greater than 50 attorneys</li><li>
Knowledge of legal concepts related to the business of the firm and the legal industry</li><li>
Familiarity with agile development methodologies</li><li>
Experience engaging with end-users to gather feedback, observe and map routines and processes</li><li>
Ability to deliver AI-enabled workflows within confidentiality/approved-AI policy constraints and governance expectations</li><li>
Excellent attention to detail</li><li>
Excellent analytical skills</li><li>
Excellent time management and project management skills, with ability to work independently to meet objectives and deadlines</li><li>
Ability to work as a member of a client-service oriented team in a professional, approachable manner</li><li>
Strong customer focus, with an emphasis on efficient and effective communications</li><li>
Solid relationship management, presentation and collaboration skills</li><li>
Unwavering ability to handle and maintain confidentiality regarding firm information, projects, client data</li><li>
Ability to work independently and take initiative while ensuring compliance with team standards in development, delivery and support of business systems</li><li>
Entrepreneurial by nature</li><li>
Ability to organize, prioritize and coordinate multiple activities often under tight timelines</li><li>
Ability to drive projects to completion and achieve goals</li><li>
Team-player with collaborative spirit</li></ul>
Cooley offers a competitive compensation and excellent benefits package and is committed to fair and equitable employment practices.
EOE.
The expected annual pay range for this position with a full-time schedule is $120,000 - $175,000. Senior level candidates may be considered for this position and would be eligible for a higher salary range based on experience. Please note that final offer amount will be dependent on geographic location, applicable experience and skillset of the candidate.
We offer a full range of elective benefits including medical, health savings account (with applicable medical plan), dental, vision, health and/or dependent care flexible spending accounts, pre-tax commuter benefits, life insurance, AD&amp;D, long-term care coverage, backup care for children and/or adults and other parental support benefits. In addition to elective benefit options, benefited employees receive firm-paid life insurance, AD&amp;D, LTD, short term medical benefits as well as 21 days of Paid Time Off (&ldquo;PTO&rdquo;) and 10 paid holidays each year. We provide generous parental leave and fertility benefits. New employees will attend a detailed benefit orientation to learn more about our many benefits and resources.</div>

Artificial Intelligence (“AI”) Solutions Engineer

Catalyst Labs

<div>
 
 About The Job ML Engineer
 
 
 
 
 Our Client
 
 
 
 Is a rapidly growing Tier 1 VC backed startup based in New York with $60 million in funding revolutionizing how outside sales and service teams work. Their AI technology captures and analyzes real-world conversations, providing full visibility into every customer interaction without the need for traditional ride-alongs.
 
 
 By turning field conversations into searchable, actionable data, they empower teams to coach more effectively, close more deals, and boost average ticket sizes. Combining cutting-edge AI with a deep understanding of field sales dynamics, this company is redefining how businesses learn from and optimize their in-person customer experiences.
 
 
 
 About Us
 
 
 
 Catalyst Labs is a leading talent agency with a specialized vertical in Applied AI, Machine Learning, and Data Science. We stand out as an agency that&rsquo;s deeply embedded in our clients&rsquo; recruitment operations.
 
 
 We collaborate directly with Founders, CTOs, and Heads of AI in those themes who are driving the next wave of applied intelligence from model optimization to productized AI workflows. We take pride in facilitating conversations that align with your technical expertise, creative problem-solving mindset, and long-term growth trajectory in the evolving world of intelligent systems.
 
 
 
 Location
 
 : New York, NY
 
 
 
 Work type
 
 : Full Time,
 
 
 
 Compensation
 
 : above market base + bonus + equity
 
 
 
 Roles &amp; Responsibilities
 
 
 
 <ul>
 <li>
 Design, build, and deploy production-grade ML systems with end-to-end ownership of the model lifecyclefrom conception to deployment and maintenance.
 </li>
 <li>
 Architect and deliver AI-powered solutions enabling natural speech interaction and real-time audio understanding.
 </li>
 <li>
 Develop and optimize ML models focused on audio data to extract business-critical insights from previously unstructured voice data.
 </li>
 <li>
 Build agents capable of operating natively on real-world audio inputs.
 </li>
 <li>
 Collaborate with cross-functional teams to shape the foundations of the AI stack, improve tooling, and drive innovation in LLM and audio ML applications.
 </li>
 <li>
 Work directly with customers to identify needs, gather feedback, and deliver impactful real-world solutions.
 </li>
 <li>
 Handle the entire AI lifecycle, including data acquisition, preprocessing, model training, deployment, inference, and monitoring in production environments.
 </li>
 <li>
 Participate in continuous improvement of the ML infrastructure and processes for scalability and performance.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
 </li>
 <li>
 1-6 years of professional experience in ML engineering.
 </li>
 <li>
 Strong programming skills in Python (TypeScript experience is a plus).
 </li>
 <li>
 Hands-on experience with ML frameworks such as PyTorch or TensorFlow.
 </li>
 <li>
 Familiarity with cloud environments and infrastructure (preferably AWS).
 </li>
 <li>
 Strong understanding of data pipeline design, real-time inference, and model monitoring.
 </li>
 <li>
 Excellent communication skills with the ability to engage directly with customers and stakeholders.
 
 
 </li>
 </ul>
 
 Core Experience
 
 
 
 <ul>
 <li>
 Proven experience building and deploying ML models into production environments.
 </li>
 <li>
 Demonstrated ability to own the full model lifecyclefrom data ingestion and model development to deployment and monitoring.
 </li>
 <li>
 Experience with audio-focused ML projects or similar domains involving unstructured data.
 </li>
 <li>
 Proficiency in building scalable data pipelines for model training and evaluation.
 </li>
 <li>
 Familiarity with FastAPI, OpenAI APIs, Baseten, LiteLLM, LiveKit, PostgreSQL, Redis, and S3 is a plus.
 </li>
 <li>
 Solid grasp of ML systems architecture, feature engineering, evaluation strategies, and deployment best practices.
 </li>
 </ul>
</div>

ML Engineer

Capital One

<div>Distinguished Data Engineer
Distinguished Data Engineers are individual contributors who strive to be diverse in thought so we visualize the problem space. At Capital One, we believe diversity of thought strengthens our ability to influence, collaborate and provide the most innovative solutions across organizational boundaries. Distinguished Engineers will significantly impact our trajectory and devise clear roadmaps to deliver next generation technology solutions.
You will work alongside our talented team of developers, machine learning experts, product managers and people leaders. Our Distinguished Engineers are leading experts in their domains, helping devise practical and reusable solutions to complex problems. You will drive innovation at multiple levels, helping optimize business outcomes while driving towards strong technology solutions.
At Capital One, we believe diversity of thought strengthens our ability to influence, collaborate and provide the most innovative solutions across organizational boundaries. You will promote a culture of engineering excellence, and strike the right balance between lending expertise and providing an inclusive environment where the ideas of others can be heard and championed. You will lead the way in creating next-generation talent for Capital One Tech, mentoring internal talent and actively recruiting to keep building our community.
Distinguished Engineers are expected to lead through technical contribution. You will operate as a trusted advisor for our key technologies, platforms and capability domains, creating clear and concise communications, code samples, blog posts and other material to share knowledge both inside and outside the organization. You will specialize in a particular subject area, but your input and impact will be sought and expected throughout the organization.<ul><li>
Deep technical experts and thought leaders that help accelerate adoption of the very best engineering practices, while maintaining knowledge on industry innovations, trends and practices</li><li>
Visionaries, collaborating on Capital One&rsquo;s toughest issues, to deliver on business needs that directly impact the lives of our customers and associates</li><li>
Role models and mentors, helping to coach and strengthen the technical expertise and know-how of our engineering and product community</li><li>
Evangelists, both internally and externally, helping to elevate the Distinguished Engineering community and establish themselves as a go-to resource on given technologies and technology-enabled capabilities.</li></ul>
Responsibilities:<ul><li>
Build awareness, increase knowledge and drive adoption of modern technologies, sharing consumer and engineering benefits to gain buy-in.</li><li>
Strike the right balance between lending expertise and providing an inclusive environment where others&rsquo; ideas can be heard and championed; leverage expertise to grow skills in the broader Capital One team</li><li>
Promote a culture of engineering excellence, using opportunities to reuse and inner source solutions where possible</li><li>
Effectively communicate with and influence key stakeholders across the enterprise, at all levels of the organization</li><li>
Operate as a trusted advisor for a specific technology, platform or capability domain, helping to shape use cases and implementation in an unified manner</li><li>
Lead the way in creating next-generation talent for Tech, mentoring internal talent and actively recruiting external talent to bolster Capital One&rsquo;s Tech talent.</li><li>
Define and champion the strategic roadmap for the adoption, governance, and cost-optimization of the data ecosystem leveraging Databricks and Snowflake on the AWS cloud.</li><li>
Lead the design and implementation of highly scalable, fault-tolerant, and cost-effective data architectures that seamlessly integrate Databricks (for complex processing/ML) and Snowflake (for warehousing/BI).</li><li>
Serve as the primary technical authority for data security and governance best practices within Databricks and Snowflake, ensuring integration with core AWS security services (e.g., IAM, KMS).</li><li>
Drive performance engineering and optimization for large-scale data ingestion and processing workloads across the Databricks/Snowflake/AWS data pipeline.</li><li>
Mentor engineering teams on the advanced features, architecture, and cost-efficient usage of Databricks, Snowflake, and related AWS services.</li><li>
Articulate and evangelize a bold technical vision for your domain</li><li>
Decompose complex problems into practical and operational solutions</li><li>
Ensure the quality of technical design and implementation</li><li>
Serve as an authoritative expert on non-functional system characteristics, such as performance, scalability and operability</li><li>
Continue learning and injecting advanced technical knowledge into our community</li><li>
Handle several projects simultaneously, balancing your time to maximize impact</li><li>
Act as a role model and mentor within the tech community, helping to coach and strengthen the technical expertise and know-how of our engineering and product community</li><li>
Ensure Code is of the highest quality &amp; standard while being an active contributor and reviewer on critical repos of the application</li><li>
Develop full stack applications with a product engineering mindset, spanning frontend and backend ecosystems that balance simplicity with flexibility</li></ul>
Basic Qualifications:<ul><li>
Bachelor&rsquo;s Degree</li><li>
At least 7 years of experience in data engineering</li><li>
At least 3 years of experience in data architecture</li><li>
At least 2 years of experience building applications in AWS</li></ul>
Preferred Qualifications:<ul><li>
Masters&rsquo; Degree</li><li>
9+ years of experience in data engineering</li><li>
3+ years of data modeling experience</li><li>
2+ years of experience with ontology standards for defining a domain</li><li>
2+ years of experience using Python, SQL or Scala</li><li>
1+ year of experience deploying machine learning models</li><li>
3+ years of experience implementing big data processing solutions on AWS</li><li>
10+ years of hands-on experience developing and architecting solutions on AWS.</li><li>
Deep proficiency and strategic experience with Databricks (e.g., Delta Lake, Unity Catalog, ML flow, performance tuning Spark workloads).</li><li>
Deep proficiency and strategic experience with Snowflake (e.g., Data Sharing, Snowpipe, external tables, security features, cost governance, advanced SQL/Stored Procedures).</li><li>
Deep practical knowledge of core AWS data services such as Amazon S3, EMR, Glue, Kinesis, and Lambda, and how they integrate with Databricks and Snowflake.</li><li>
Experience with Infrastructure as Code (IaC) tools (e.g., Terraform) to automate the deployment and management of Databricks and Snowflake environments on AWS.</li><li>
Relevant professional certifications such as AWS Certified Solutions Architect - Professional or Snowflake/Databricks certifications (e.g., Certified SnowPro Advanced Architect).</li><li>
10+ years of professional experience coding in commonly used languages like Java, Python, Go, JavaScript/TypeScript, Swift, etc.</li><li>
8+ years of professional experience in the full lifecycle of system development, from conception through architecture, implementation, testing, deployment and production support.</li><li>
Experience in applying Artificial Intelligence or Machine Learning concepts to engineering challenges (e.g., anomaly detection, test optimization, intelligent testing).</li><li>
Deep practical knowledge of Site Reliability Engineering (SRE) principles, chaos engineering, and advanced Observability tooling (e.g., Open Telemetry, Prometheus, Tracing)</li><li>
Experience in implementing Artificial Intelligence or Artificial Intelligence-enabled solutions.</li></ul>
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position
The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.
New York, NY: $293,600 - $335,100 for Distinguished Data Engineer 
Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate&rsquo;s offer letter.
This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.
Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.
This role is expected to accept applications for a minimum of 5 business days.
No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City&rsquo;s Fair Chance Act; Philadelphia&rsquo;s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.
If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.
For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com
Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.
Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).</div>

Distinguished Data Engineer

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