software engineer

data engineer

data scientist

ai engineer

data analyst

applied scientist

Capital One

<div>
 
 Overview
 
 
 
 At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent &mdash; along with our deep experience in machine learning &mdash; position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI &amp; ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build.
 
 
 
 Team Description:
 
 
 
 The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact.
 
 
 
 In this role, you will:
 
 
 
 <ul>
 <li>
 Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.
 </li>
 <li>
 Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.
 </li>
 <li>
 Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more.
 </li>
 <li>
 Invent and introduce state-of-the-art LLM optimization techniques to improve the performance &mdash; scalability, cost, latency, throughput &mdash; of large scale production AI systems.
 </li>
 <li>
 Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.
 
 
 </li>
 </ul>
 
 The Ideal Candidate:
 
 
 
 <ul>
 <li>
 You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good.
 </li>
 <li>
 Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production.
 </li>
 <li>
 You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven.
 </li>
 <li>
 You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss.
 </li>
 <li>
 You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown.
 
 
 </li>
 </ul>
 
 Basic Qualifications:
 
 
 
 <ul>
 <li>
 Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies
 </li>
 <li>
 At least 4 years of experience programming with Python, Go, Scala, or Java
 
 
 </li>
 </ul>
 
 Preferred Qualifications:
 
 
 
 <ul>
 <li>
 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)
 </li>
 <li>
 Experience designing, developing, delivering, and supporting AI services
 </li>
 <li>
 Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang
 </li>
 <li>
 Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost
 </li>
 <li>
 Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production
 
 
 </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.
 
 
 McLean, VA: $197,300 - $225,100 for Lead AI Engineer
 
 
 New York, NY: $215,200 - $245,600 for Lead AI Engineer
 
 
 San Francisco, CA: $215,200 - $245,600 for Lead AI Engineer
 
 
 San Jose, CA: $215,200 - $245,600 for Lead AI 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>

Lead AI Engineer (FM Hosting, LLM Inference)

<div>
 At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent &mdash; along with our deep experience in machine learning &mdash; position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI &amp; ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build.
 
 
 
 
 Team Description:
 
 
 
 
 The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact.
 
 
 
 
 In this role, you will:
 
 
 
 
 <ul>
 <li>
 Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.
 </li>
 <li>
 Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.
 </li>
 <li>
 Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more.
 </li>
 <li>
 Invent and introduce state-of-the-art LLM optimization techniques to improve the performance &mdash; scalability, cost, latency, throughput &mdash; of large scale production AI systems.
 </li>
 <li>
 Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.
 
 
 </li>
 </ul>
 
 
 The Ideal Candidate:
 
 
 
 
 <ul>
 <li>
 You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good.
 </li>
 <li>
 Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production.
 </li>
 <li>
 You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven.
 </li>
 <li>
 You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss.
 </li>
 <li>
 You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown.
 
 
 </li>
 </ul>
 
 
 Basic Qualifications:
 
 
 
 
 <ul>
 <li>
 Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies
 </li>
 <li>
 At least 4 years of experience programming with Python, Go, Scala, or Java
 
 
 </li>
 </ul>
 
 
 Preferred Qualifications:
 
 
 
 
 <ul>
 <li>
 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)
 </li>
 <li>
 Experience designing, developing, delivering, and supporting AI services
 </li>
 <li>
 Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang
 </li>
 <li>
 Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost
 </li>
 <li>
 Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production
 
 
 </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.
 
 
 Cambridge, MA: $197,300 - $225,100 for Lead AI Engineer
 
 
 McLean, VA: $197,300 - $225,100 for Lead AI Engineer
 
 
 New York, NY: $215,200 - $245,600 for Lead AI Engineer
 
 
 San Francisco, CA: $215,200 - $245,600 for Lead AI Engineer
 
 
 San Jose, CA: $215,200 - $245,600 for Lead AI 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>

Lead AI Engineer (MLX, Agentic AI, Gen AI platform Services)

<div>
 
 Overview
 
 
 
 At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent &mdash; along with our deep experience in machine learning &mdash; position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI &amp; ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build.
 
 
 
 Team Description:
 
 
 
 The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact.
 
 
 
 In this role, you will:
 
 
 
 <ul>
 <li>
 Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.
 </li>
 <li>
 Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.
 </li>
 <li>
 Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more.
 </li>
 <li>
 Invent and introduce state-of-the-art LLM optimization techniques to improve the performance &mdash; scalability, cost, latency, throughput &mdash; of large scale production AI systems.
 </li>
 <li>
 Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.
 
 
 </li>
 </ul>
 
 The Ideal Candidate:
 
 
 
 <ul>
 <li>
 You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good.
 </li>
 <li>
 Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production.
 </li>
 <li>
 You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven.
 </li>
 <li>
 You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss.
 </li>
 <li>
 You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown.
 
 
 </li>
 </ul>
 
 Basic Qualifications:
 
 
 
 <ul>
 <li>
 Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies
 </li>
 <li>
 At least 4 years of experience programming with Python, Go, Scala, or Java
 
 
 </li>
 </ul>
 
 Preferred Qualifications:
 
 
 
 <ul>
 <li>
 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)
 </li>
 <li>
 Experience designing, developing, delivering, and supporting AI services
 </li>
 <li>
 Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang
 </li>
 <li>
 Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost
 </li>
 <li>
 Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production
 
 
 </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.
 
 
 McLean, VA: $197,300 - $225,100 for Lead AI Engineer
 
 
 New York, NY: $215,200 - $245,600 for Lead AI Engineer
 
 
 Cambridge, MA: $197,300 - $225,100 for Lead AI Engineer
 
 
 San Francisco, CA: $215,200 - $245,600 for Lead AI Engineer
 
 
 San Jose, CA: $215,200 - $245,600 for Lead AI 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>

Lead AI Engineer ( MLX, Gen AI Platform Services, Agentic AI)

Security Engineer, Applied AI

Translucent AI

<div>
 
 Role Details
 
 
 
 <ul>
 <li>
 Full-Time
 </li>
 <li>
 Office Location - New York City (hybrid)
 
 
 </li>
 </ul>
 
 Why Translucent
 
 
 
 Healthcare providers drive $2.5 trillion in medical expenditures annually &mdash; and operate on razor-thin 2&ndash;5% margins. Despite these stakes, the finance teams behind these organizations are buried in spreadsheets, manual data pulls, and disconnected systems, spending more time finding and cleaning data than actually using it to make decisions.
 
 
 Translucent is changing that. We're building the agentic AI platform designed exclusively for healthcare finance&mdash; giving every finance team, department, service line their own arsenal of AI Agents that run 24/7, understand their specific data, business logic, and workflows.
 
 
 Founded in 2024 and backed by GV, NEA, FPV, and Virtue, we've already been deployed by healthcare organizations managing over $5 billion in combined revenue. The product-market fit is real, the problem is massive, and we're just getting started. If you want to work at the intersection of AI and one of the most complex, consequential industries in the world, this is the place.
 
 
 
 Role Overview
 
 
 
 We're looking for an AI Engineer to help build the agentic platform at the core of Translucent: the AI financial platform transforming how healthcare organizations make business decisions.
 
 
 You'll work hands-on across R&amp;D and platform engineering &mdash; improving the underlying agent capabilities every team builds on, rather than configuring agents for a single customer. You'll standardize the tool surfaces new capabilities plug into, make the agent platform ready to integrate across products, and own the evals, context, and harness engineering that make it reliable enough for healthcare finance. You'll match the right agentic architecture to each use case, turn core capabilities into an ecosystem others build on, and own quality end-to-end.
 
 
 If you are energized by fast-paced environments, love sweating the details of production AI systems, partnering closely with product and design, and seeing your work in customers' hands quickly, you'll feel at home here.
 
 
 
 What You&rsquo;ll Do
 
 
 
 <ul>
 <li>
 Standardize tool and skill surfaces &mdash; define the contracts (MCP-style tool, connector, and skill interfaces) that let us add new capabilities continuously without destabilizing the platform as it grows
 </li>
 <li>
 Make the agent platform integration-ready &mdash; build the connective tissue so agents, tools, context, and data compose cleanly across products, and match the right agentic architecture to each use case
 </li>
 <li>
 Own evals and benchmarks &mdash; build production-grade eval harnesses, replay, and benchmarks for agentic AI, and gate releases on them; in healthcare finance, accuracy is non-negotiable
 </li>
 <li>
 Lead context and harness engineering &mdash; establish best practices for grounding agents in each customer's business rules and data, and for the control loops that keep outputs reliable
 </li>
 <li>
 Fine-tune and evaluate models &mdash; fine-tune in-house and open-source models, benchmark them against frontier baselines, and make the build-vs-buy calls on model, framework, and infra
 </li>
 <li>
 Turn capabilities into an ecosystem &mdash; build reusable core capabilities that translate across features and products, and ship them end-to-end with product and design
 
 
 </li>
 </ul>
 
 What You Have
 
 
 
 <ul>
 <li>
 3+ years of software engineering experience, with meaningful production work in Python
 </li>
 <li>
 Direct experience shipping LLM-powered or agentic systems in production &mdash; not just prototypes. You know where models fail and how to make them reliable
 </li>
 <li>
 Hands-on experience with at least one modern agent framework (LangGraph, Google ADK, LlamaIndex, Claude Agent SDK, or equivalent), and a clear point of view on what to use vs. build
 </li>
 <li>
 Production evals and benchmarking &mdash; you've built eval harnesses and benchmarks that gate real releases, not one-off spot checks
 </li>
 <li>
 Context engineering &mdash; grounding agents through retrieval, context layers, and knowledge transfer so outputs match a specific org or user
 </li>
 <li>
 Comfort with the data and retrieval layer &mdash; SQL, BigQuery or a comparable warehouse, embeddings, and vector search
 </li>
 <li>
 A bias toward shipping &mdash; you take an ambiguous problem to a working V1 fast, then iterate
 
 
 </li>
 </ul>
 
 Plus deep, demonstrable expertise in at least one (ideally two) of the following:
 
 
 
 <ul>
 <li>
 Tool-surface and connector platform engineering &mdash; standardized tool/skill contracts (e.g., MCP) and connector ecosystems that scale without breaking
 </li>
 <li>
 Harness and loop engineering &mdash; agent control loops, orchestration, and inference harnesses; right-sizing agent architecture per use case and keeping it reliable at scale
 </li>
 <li>
 Open-source and in-house model fine-tuning &mdash; fine-tuning open models and benchmarking them against frontier baselines
 </li>
 <li>
 Production context-layer engineering &mdash; systems that capture business rules and preferences and feed them to agents reliably
 
 
 </li>
 </ul>
 
 Nice to Have
 
 
 
 <ul>
 <li>
 Experience with healthcare finance, accounting, or other structured financial data &mdash; or genuine curiosity about it
 </li>
 <li>
 Applied ML or model-evaluation research background
 </li>
 <li>
 Open-source contributions to agent or LLM tooling
 </li>
 <li>
 Experience designing tool-use APIs or developer-facing AI products
 </li>
 <li>
 Familiarity with our stack: Vertex AI (Gemini, Claude on Vertex), GenKit, MCP, BigQuery
 
 
 </li>
 </ul>
 
 Experience Level
 
 
 
 We're looking for engineers who own meaningful surface area and drive work forward independently. You'll bring sharp judgment on architecture and build-vs-buy trade-offs under ambiguity, a bias toward shipping a working V1 fast, and the craft to make agentic systems reliable enough for healthcare finance &mdash; not just demos.
 
 
 https://www.translucent.co/
 
 
 
 Base Salary
 
 : $175,000-$275,000 USD + equity
</div>

AI Engineer

Ameriprise Financial

<div>About Our Company 
We&rsquo;re a diversified financial services leader with more than $1.5 trillion in assets under management, administration and advisement as of year-end 2024. Our team of 22,000 people across 19 countries, serves more than 3.5 million individual, small business and institutional clients. We are a longstanding leader in financial planning and advice, a global asset manager and an insurer. Our unwavering focus on our clients and strong financial foundation connects each of our unique businesses &ndash; Ameriprise Financial, Columbia Threadneedle Investments and RiverSource Insurance and Annuities. Here, we foster meaningful careers, invest in the future, and make a difference for clients, institutions and communities around the world.
Job Description
The VP-Forward Deployed Engineer operates at the intersection of investment strategy, quantitative analysis and applied artificial intelligence. The position is responsible for partnering closely with portfolio management and investment research teams to identify opportunities, design solutions, and develop, prototype, and deploy LLM-enabled tools that enhance investment decision-making and research processes. Combines investment management knowledge with software engine capabilities to translate investment ideas and research needs into scalable technology solutions.
Key Responsibilities<ul><li>
Serve as a trusted advisor to investment leaders, translating investment strategies, research priorities, and business challenges into innovative AI-enabled solutions that improve investment outcomes and organizational efficiency.</li><li>
Drive the design and delivery of proof-of-concept and production-ready AI capabilities, leveraging advanced analytics, machine learning, and LLM technologies to accelerate investment insights and decision-making.</li><li>
Partner across Investments, Technology, Data, Risk, and Compliance functions to ensure solutions meet enterprise standards for security, governance, scalability, and regulatory compliance.</li><li>
Influence the AI and investment technology roadmap by identifying high-value opportunities, evaluating emerging capabilities, and promoting adoption of innovative solutions across the investment organization.</li><li>
Lead the transition of successful prototypes into sustainable enterprise capabilities, partnering with engineering and platform teams to scale solutions and realize long-term business value.</li></ul> 
Required Qualifications<ul><li>
10+ years of combined experience across investment management, quantitative research/strategy, and hands-on software or AI engineering, with demonstrated success taking investment problems from concept to working solution.</li><li>
Direct experience working alongside trading desks, portfolio managers, or investment researchers, with desk strategist, quant strat, or research technologist backgrounds strongly preferred.</li><li>
Hands-on experience building and shipping LLM enabled/integrated applications: RAG/embeddings, agentic workflows, prompt engineering, API integration.</li><li>
Strong Python development skills producing production-quality code.</li><li>
Expertise with cloud infrastructure and modern software practices (CI/CD, version control, API design).</li><li>
Fluency in at least one asset class (equities, fixed income, multi-asset, or macro) at a level where you can challenge and contribute to investment discussions, not just support them.</li><li>
Track record of delivering secure, auditable AI solutions in a regulated environment, partnering with risk and compliance.</li></ul> 
Preferred Qualifications<ul><li>
Direct experience supporting front-office investment teams (portfolio managers, analysts, researchers, traders).</li><li>
Familiarity with agent frameworks and orchestration tools (LangChain, LangGraph, LlamaIndex, MCP) and vector databases.</li><li>
Experience building internal copilots, research assistants, or document-intelligence tools.</li><li>
CFA, FRM, or equivalent investment credential.</li><li>
Track record of shipping AI or analytics solutions that produced measurable, real-world outcomes.</li></ul>
Visa Sponsorship 
Applicants must have a valid work authorization that does not now, or in the future, require visa sponsorship for employment in the United States (e.g., H-1B, F-1 CPT, F-1 OPT, TN).
In-Office Collaboration 
We are a client-centric, relationship-based business. Working together, in-person, is foundational to how we achieve results. By fostering a culture of face-to-face collaboration, idea sharing, productivity and personal connection, we deliver for our stakeholders &mdash; clients, advisors, employees and shareholders. Our employees work in the office at least four (4) days per week, with flexibility to work from home one (1) day per week. Some roles may require additional in-office time or different in-office expectations, and specific requirements will be discussed during the hiring process. 
Base Pay Salary
The estimated base salary for this role is $242,100 - $332,900 / year. We have a pay-forperformance compensation philosophy. Your initial total compensation may vary based on job-related knowledge, skills, experience, and geographical work location. In addition, most of our roles are eligible for variable pay in the form of bonus, commissions, and/or long-term incentives depending on the role. We also have a competitive and comprehensive benefits program that supports all aspects of your health and well-being, including but not limited to vacation time, sick time, 401(k), and health, dental and life insurances.<div><div><div><div><div><div><div>
Full-Time/Part-Time</div></div></div></div></div></div></div>
Full time<div><div><div><div><div><div><div>
Exempt/Non-Exempt</div></div></div></div></div></div></div>
Exempt<div><div><div><div><div><div><div>
Job Family Group</div></div></div></div></div></div></div>
Data<div><div><div><div><div><div><div>
Line of Business
</div></div></div></div></div></div></div>TECH Technology
Ameriprise Financial is an equal opportunity employer. We consider all qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, gender expression, national origin, ancestry, age, physical or mental disability, medical condition, pregnancy, military status, veteran status, genetic information, citizenship, disability status, marital status, family status or any other basis prohibited by law.
We are committed to fostering an inclusive and accessible recruitment process for individuals with disabilities. If you require a reasonable accommodation to participate in the application or interview process, speak to your recruiter to discuss how we can support you.</div>

Vice President - Forward Deployed Engineer

Snowflake

<div>At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don&rsquo;t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset &mdash; who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done.
We are a visionary and innovative industry expert team with a track record of architecting, building, and taking solutions to market applicable to various sub-verticals across financial services, spanning retail and commercial banking, lending and payments.
There is only one Data Cloud. Snowflake's founders started from scratch and designed a data platform built for the cloud that is effective, affordable, and accessible to all data users. But it didn't stop there. They engineered Snowflake to power the Data Cloud, where thousands of organizations unlock the value of their data with near-unlimited scale, concurrency, and performance. This is our vision: a world with endless insights to tackle the challenges and opportunities of today and reveal the possibilities of tomorrow.
Are you passionate about taking new ideas and innovation to market? Have you successfully applied technology to solve business problems in core banking? If so, we have a strategic opportunity to use your expertise across Data, Cloud, and AI to drive transformational changes across the financial services industry in a highly visible role collaborating with internal and external leadership.
Snowflake is seeking a seasoned Financial Services Industry Architect with deep, hands-on experience designing and delivering transformation initiatives powered by data, analytics, and AI. The ideal candidate has worked directly with banks, financial services organizations to modernize core systems, unify transactional and risk data, and translate business priorities into scalable technical architectures and measurable business outcomes.
You will act as a visionary and innovative industry expert with the opportunity to apply your successful track record of architecting, building, and taking solutions to market applicable to various sub-verticals across the financial services ecosystem and critical workloads in our customer footprint.
IN THIS ROLE YOU WILL GET TO:<ul><li>
Partner with customers on strategic opportunities: You will drive customer engagement in strategic deals where your industry expertise can help drive Snowflake adoption. You'll build trusted relationships with executives, chief data officers, chief risk officers, and enterprise data architects at banks and finance organizations, acting as a trusted advisor who blends business and technical context to advance opportunities.</li><li>
Innovate and design solutions: Working with the Industry GTM team, you'll translate core banking use cases, challenges, and opportunities into data-driven and AI-powered solutions and architecture. This includes creating end-to-end architectures and future-state blueprints, and demo showcases that embed AI/ML and agentic flows into solutions such as fraud detection, credit risk modeling, regulatory reporting, and customer 360.</li><li>
Drive repeatability and scale: You'll lead strategic initiatives by building repeatable enterprise architectures and solution assets for the banking industry that can be leveraged for global adoption. Your deliverables will include persona use case journeys and system/application architecture, demo showcases that integrate Snowflake into a customer's broader financial services solutions portfolio and ecosystem. You'll also scale your expertise through field enablement and by creating workshops and playbooks.</li><li>
Influence the product roadmap: Act as a conduit to the product teams, providing structured feedback based on banking industry needs and customer requirements to help shape Snowflake's product roadmap.</li><li>
Be a thought leader: Drive technical thought leadership for the financial services industry through blogs, talks, and field enablement. You will also be a key contributor to industry marketing activities including webinars and conferences such as Money20/20, Sibos, InsureTech Connect, and LIMRA.</li></ul>
ON DAY ONE WE WILL EXPECT YOU TO HAVE:<ul><li>
10+ years of architecture experience building, consulting to, and/or implementing technology for core banking and/or financial services organizations</li><li>
Expert in financial services data topics and well-versed in the overall challenges and opportunities impacting the industry; ability to map data requirements and processes for the major functional areas of core banking (Retail &amp; Commercial Lending, Payments, Treasury, Risk &amp; Compliance, Finance)</li><li>
Ability to consultatively engage with customers to understand pain points, challenges, and come up with right-fit solution architecture using the latest data and AI technologies</li><li>
Broad range of experience with technical and design direction including large-scale database and/or data warehouse technology, ETL, analytics, and public cloud technologies</li><li>
Understanding of Data Science &amp; Machine Learning concepts and applications in financial services &mdash; including credit scoring, fraud detection, and AML/transaction monitoring</li><li>
Familiarity with key sources of enterprise financial services data and technologies including core banking platforms (e.g., Temenos, FIS, Fiserv, Finacle), risk and compliance systems, actuarial tools (e.g., ResQ, Remetrica), payment networks, CRMs, and third-party data providers</li><li>
Understanding of financial services regulatory and compliance frameworks (Basel III/IV, DORA, IFRS 9/17, Solvency II, BCBS 239, AML/KYC, NAIC, state DOI reporting) and the data demands they create</li><li>
Outstanding presentation skills to both technical and executive audiences, whether impromptu on a whiteboard or using presentations and demos</li><li>
Exceptional communication skills, with the ability to explain complex technical concepts clearly to architects, engineering leaders, risk officers, operations leaders, business executives, and regulatory stakeholders</li><li>
Experience working with senior executives and an ability to quickly establish credibility with senior leadership</li><li>
Bachelor's Degree required; Master's Degree in computer science, engineering, mathematics, finance, actuarial science, or related fields, or equivalent experience preferred</li><li>
The ability to travel to customer sites, industry events, and other related events as required</li><li>
Strong knowledge of SQL, Python with hands-on experience is required; experience in Java, Scala, or other languages is a plus</li><li>
3+ years of Cloud Provider (AWS, Azure, or GCP) customer-facing architecture development experience</li></ul>
WHAT ARE THE TYPICAL GOALS FOR THE ROLE?
Proactive customer guidance:<ul><li>
Technical Industry Overview and Architecture:How is the banking industry adopting Snowflake, and which industry value drivers does Snowflake attach to?</li><li>
Technical Use Case Overviews:Extend use case presentations with how financial services use cases might be addressed &mdash; including technical architectures and key decision points for risk, compliance, banking, and lending workloads.</li><li>
Ecosystem partner engagement:Does the customer need interface or vendor guidance with financial services ecosystem partners (e.g., FIS, Fiserv, Temenos, Verisk, LexisNexis Risk Solutions, MSCI)? Is there an ecosystem participant without a Data Cloud presence we should introduce to the wider Snowflake team? We can facilitate these conversations and advocate for the customer and the vendor.</li><li>
Solution architecture and review:Snowflake has a diverse ecosystem of financial services industry participants with domain-specific solutions to a wide range of use cases; domain-specific architecture reviews play a key role.</li><li>
Strategic stakeholder alignment:C-level and direct reports may require strategic, longer-running relationships that maintain consistency and alignment across business units and use cases &mdash; particularly in large global banks. The Industry Architect role can help maintain global consistency of vision and assist individual geographies.</li><li>
Strong alignment with the Financial Services Industry Team</li><li>
Technical industry trend PoV:Data Mesh, Data Vault, GenAI, Data Lakes vs. Warehouses vs. Lakehouses &mdash; view these technical trends through a financial services lens, including case studies on real-time fraud detection, open banking data sharing, and regulatory data lineage.</li><li>
Snowdays: Bring in the wider team to complement the customer's point of view with a broader industry perspective, including bespoke solution/lab setups for banking</li><li>
RFP support: Some RFPs have a financial services industry backdrop and may request information on the Financial Services Data Cloud, or otherwise require a perspective on specific regulatory, risk, or operational topics.</li></ul> 
Internal Engagement
We are always looking for ways to scale our offering. We welcome opportunities to gather a group of SEs to drive and foster better industry alignment and knowledge sharing. Creating scalable content and driving adoption of key use cases is the primary goal for the role, so finding ways to spread the message both internally and externally is critical.
Partner Engagement
Our team is always looking for new and innovative ways to solve key use cases. This includes engaging with key financial services ecosystem partners to develop industry best practices, architectures, and demos.
Industry Events
Our team of specialists is most likely already involved with key industry events such as Money20/20, Sibos, InsureTech Connect, and LIMRA. If there is something that makes sense to bring us into, please let us know how we can help.
Every Snowflake employee is expected to follow the company's confidentiality and security standards for handling sensitive data. Snowflake employees must abide by the company's data security plan as an essential part of their duties. It is every employee's duty to keep customer information secure and confidential.
Snowflake is growing fast, and we&rsquo;re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake.
How do you want to make your impact?
For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information: careers.snowflake.com
The following represents the expected range of compensation for this role:<ul><li>
This role is eligible to participate in Snowflake's commission plan and it is common for employees in this role to receive total on-target earnings of $249,600 - $327,600. The estimated base salary for this role is $187,200 - $245,700.</li><li>
Additionally, this role is eligible to participate in Snowflake&rsquo;s equity plan.</li></ul>
The successful candidate&rsquo;s starting salary will be determined based on permissible, non-discriminatory factors such as skills, experience, and geographic location. This role is also eligible for a competitive benefits package that includes: medical, dental, vision, life, and disability insurance; 401(k) retirement plan; flexible spending &amp; health savings account; at least 12 paid holidays; paid time off; parental leave; employee assistance program; and other company benefits.
To comply with pay transparency requirements and other statutes, you can notify us if you believe that a job posting is not compliant by completing this form.</div>

Project Manager

Explore 7+ Applied scientist in New York this September. Find roles across top companies and apply now to boost your career.