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Job Description Job Description Genesis10 is currently seeking a Innovation Principal Engineer for a Contract-to-Hire opportunity. This position can work hybrid or can work remotely in the footprint locations of Columbus, OH; Minnetonka, MN; Atlanta, GA: Dallas, TX; Detroit, MI; Chicago, IL; Charlotte, NC; Birmingham, AL; Tupelo, MS; Pittsburgh, PA; Cleveland, OH; Akron, OH and Cincinnati, OH. Compensation: $100.00 - $110.00 per hour, W2, based on qualifications Position Overview: This position will be responsible for driving this organizations most complex innovation initiatives by designing and building end-to-end, production-grade prototypes and reusable technology assets, including AI-enabled and agentic applications within Google Cloud, while setting high engineering standards for solution architecture, application design, security, governance, and delivery acceleration across the Technology Innovation portfolio. This role requires strong hands-on full-stack engineering skills, the mindset of a startup innovator in a large organization, deep experience building AI-integrated applications end-to-end, developing APIs and user experiences, and the ability to operate independently with limited supervision in a fast-paced innovation environment. The ideal candidate will bring demonstrated production experience with Vertex AI, Gemini, agent frameworks, AI gateway/model-proxy patterns, and enterprise-grade deployment of AI workloads. Key Responsibilities: Lead the design and delivery of high-impact innovation solutions aligned with the organization's business goals and technology trends in financial services Architect and build end-to-end prototypes, production-ready solutions, and reusable assets, including AI-enabled applications, agentic workflows, APIs, workflow automations, and integrations Translate AI innovation concepts, including GenAI, RAG, and agentic patterns, into production-grade applications using Google Cloud technologies such as Vertex AI and Gemini Architect and implement agent-based and multi-agent systems using frameworks such as Google ADK, Agent Engine, LangGraph, or equivalent technologies Design and oversee cloud-native deployment patterns for AI applications and agent services, ideally using Cloud Run, CI/CD, observability, logging, monitoring, and secure environment configuration Architect or integrate with AI gateways and model-proxy layers supporting model routing, authentication, access controls, guardrails, policy enforcement, and usage governance Define grounding and Retrieval-Augmented Generation (RAG) patterns using Vertex AI Search / Discovery Engine or comparable enterprise retrieval technologies Establish AI governance patterns covering token usage, model consumption, cost management, security controls, guardrails, evaluation, and observability Build solutions with a future-proof mindset, laying a solid foundation for development and preventing the need for costly redesigns Establish and evolve engineering standards for innovation delivery, including reference architectures, reusable templates, code quality, API patterns, agent orchestration patterns, integration patterns, and secure AI development standards Partner with other technology teams to align on enterprise architecture, identity / access patterns, data access, compliance needs, private networking, and reuse opportunities Evaluate emerging technologies and developer tooling, including Digital Assets, AI-assisted development, orchestration frameworks, app frameworks, integration approaches, and AI governance technologies, and assess applicability to the client's environment Drive technical problem-solving across ambiguous domains; proactively decompose work into deliverable increments and lead execution to complete finished outcomes Provide technical mentorship and guidance to engineers, helping improve development velocity, quality, architectural consistency, and confidence across the team Contribute to innovation reporting by summarizing progress, decisions, tradeoffs, and outcomes in a clear way for senior stakeholders Champion a culture of innovation and forward thinking, educating teams about new possibilities and bring an "art of the possible" mindset to problem-solving Primary Requirements: Bachelor's degree in Computer Science, Information Technology, Artificial Intelligence, Machine Learning, or a related technical field Demonstrated hands-on experience building applications end-to-end (backend + integration + UI), including APIs and workflow automation solutions Deep hands-on Google Cloud engineering experience with demonstrated production deployment of applications and AI workloads within GCP Demonstrated production experience building AI-enabled applications using Vertex AI and Gemini; experience should extend beyond using Gemini or other GenAI tools solely as coding assistants Demonstrated hands-on experience architecting and building agentic or multi-agent systems using Google ADK, Agent Engine, LangGraph, or comparable orchestration frameworks Demonstrated experience building AI-enabled applications involving GenAI, RAG, model integration, evaluation, guardrails, and production deployment Strong experience designing AI gateway, LLM gateway, or model-proxy patterns covering model routing, authentication, security, policy enforcement, and governance Expert-level software engineering and application architecture skills with the ability to independently lead complex initiatives from concept to execution Comfortable operating in a fast-paced, ambiguous environment while managing multiple priorities and driving workplans proactively 10+ years of experience in software engineering, technology architecture, and end-to-end innovative solution delivery Desired Qualifications: Experience building innovative digital products in a regulated environment (financial services preferred) with strong security and risk-awareness Experience deploying AI solutions in highly controlled environments using technologies or patterns such as VPC Service Controls (VPC-SC), private networking, DLP, and secure service-to-service communication Strong API design skills, integration patterns, and experience building services that can be reused across multiple use cases Experience deploying agentic and AI-enabled applications using Google Cloud Run or comparable cloud-native container platforms Experience implementing grounding/RAG solutions using Vertex AI Search / Discovery Engine or comparable enterprise retrieval technologies Experience implementing AI safety and security controls using Model Armor or comparable technologies Experience managing token usage, model consumption, observability, and AI-related cost governance Experience with modern front-end frameworks and rapid prototyping approaches (e.g., React/Next.js or equivalent), plus strong backend development depth Strong hands-on software engineering experience using one or more modern programming languages (e.g., Java, Python, TypeScript/JavaScript, or similar), with the ability to rapidly learn and apply new technologies as needed Demonstrated success creating reusable accelerators, including templates, libraries, reference implementations, AI patterns, and governance frameworks that scale delivery across teams Experience with AWS Bedrock, Azure OpenAI, or comparable AI platforms is beneficial when combined with demonstrated hands-on Google Cloud AI deployment experience Strong communication skills with the ability to explain architecture decisions, tradeoffs, and outcomes to technical and non-technical audiences Experience building with a product-centric mindset and ability to iteratively delivery; ability to create momentum while maintaining engineering discipline Only candidates available and ready to work directly as Genesis10 employees will be considered for this position. If you have the described qualifications and are interested in this exciting opportunity, please apply! Ranked a Top Staffing Firm in the U.S. by Staffing Industry Analysts for six consecutive years, Genesis10 puts thousands of consultants and employees to work across the United States every year in contract, contract-for-hire, and permanent placement roles. With more than 300 active clients, Genesis10 provides access to many of the Fortune 100 firms and a variety of mid-market organizations across the full spectrum of industry verticals. For contract roles, Genesis10 offers the benefits listed below. If this is a perm-placement opportunity, our recruiter can talk you through the unique benefits offered for that particular client. Benefits of Working with Genesis10: Access to hundreds of clients, most who have been working with Genesis10 for 5-20+ years The opportunity to have a career-home in Genesis10; many of our consultants have been working exclusively with Genesis10 for years Access to an experienced, caring recruiting team (more than 7 years of experience, on average) Behavioral Health Platform Medical, Dental, Vision Health Savings Account Voluntary Hospital Indemnity (Critical Illness & Accident) Voluntary Term Life Insurance 401K Sick Pay (for applicable states/municipalities) Commuter Benefits (Dallas, NYC, SF, and Illinois) For multiple years running, Genesis10 has been recognized as a Top Staffing Firm in the U.S., as a Best Company for Work-Life Balance . click apply for full job details

Job Description Job Description Genesis10 is currently seeking a Innovation Principal Engineer for a Contract-to-Hire opportunity. This position can work hybrid or can work remotely in the footprint locations of Columbus, OH; Minnetonka, MN; Atlanta, GA: Dallas, TX; Detroit, MI; Chicago, IL; Charlotte, NC; Birmingham, AL; Tupelo, MS; Pittsburgh, PA; Cleveland, OH; Akron, OH and Cincinnati, OH. Compensation: $100.00 - $110.00 per hour, W2, based on qualifications Position Overview: This position will be responsible for driving this organizations most complex innovation initiatives by designing and building end-to-end, production-grade prototypes and reusable technology assets, including AI-enabled and agentic applications within Google Cloud, while setting high engineering standards for solution architecture, application design, security, governance, and delivery acceleration across the Technology Innovation portfolio. This role requires strong hands-on full-stack engineering skills, the mindset of a startup innovator in a large organization, deep experience building AI-integrated applications end-to-end, developing APIs and user experiences, and the ability to operate independently with limited supervision in a fast-paced innovation environment. The ideal candidate will bring demonstrated production experience with Vertex AI, Gemini, agent frameworks, AI gateway/model-proxy patterns, and enterprise-grade deployment of AI workloads. Key Responsibilities: Lead the design and delivery of high-impact innovation solutions aligned with the organization's business goals and technology trends in financial services Architect and build end-to-end prototypes, production-ready solutions, and reusable assets, including AI-enabled applications, agentic workflows, APIs, workflow automations, and integrations Translate AI innovation concepts, including GenAI, RAG, and agentic patterns, into production-grade applications using Google Cloud technologies such as Vertex AI and Gemini Architect and implement agent-based and multi-agent systems using frameworks such as Google ADK, Agent Engine, LangGraph, or equivalent technologies Design and oversee cloud-native deployment patterns for AI applications and agent services, ideally using Cloud Run, CI/CD, observability, logging, monitoring, and secure environment configuration Architect or integrate with AI gateways and model-proxy layers supporting model routing, authentication, access controls, guardrails, policy enforcement, and usage governance Define grounding and Retrieval-Augmented Generation (RAG) patterns using Vertex AI Search / Discovery Engine or comparable enterprise retrieval technologies Establish AI governance patterns covering token usage, model consumption, cost management, security controls, guardrails, evaluation, and observability Build solutions with a future-proof mindset, laying a solid foundation for development and preventing the need for costly redesigns Establish and evolve engineering standards for innovation delivery, including reference architectures, reusable templates, code quality, API patterns, agent orchestration patterns, integration patterns, and secure AI development standards Partner with other technology teams to align on enterprise architecture, identity / access patterns, data access, compliance needs, private networking, and reuse opportunities Evaluate emerging technologies and developer tooling, including Digital Assets, AI-assisted development, orchestration frameworks, app frameworks, integration approaches, and AI governance technologies, and assess applicability to the client's environment Drive technical problem-solving across ambiguous domains; proactively decompose work into deliverable increments and lead execution to complete finished outcomes Provide technical mentorship and guidance to engineers, helping improve development velocity, quality, architectural consistency, and confidence across the team Contribute to innovation reporting by summarizing progress, decisions, tradeoffs, and outcomes in a clear way for senior stakeholders Champion a culture of innovation and forward thinking, educating teams about new possibilities and bring an "art of the possible" mindset to problem-solving Primary Requirements: Bachelor's degree in Computer Science, Information Technology, Artificial Intelligence, Machine Learning, or a related technical field Demonstrated hands-on experience building applications end-to-end (backend + integration + UI), including APIs and workflow automation solutions Deep hands-on Google Cloud engineering experience with demonstrated production deployment of applications and AI workloads within GCP Demonstrated production experience building AI-enabled applications using Vertex AI and Gemini; experience should extend beyond using Gemini or other GenAI tools solely as coding assistants Demonstrated hands-on experience architecting and building agentic or multi-agent systems using Google ADK, Agent Engine, LangGraph, or comparable orchestration frameworks Demonstrated experience building AI-enabled applications involving GenAI, RAG, model integration, evaluation, guardrails, and production deployment Strong experience designing AI gateway, LLM gateway, or model-proxy patterns covering model routing, authentication, security, policy enforcement, and governance Expert-level software engineering and application architecture skills with the ability to independently lead complex initiatives from concept to execution Comfortable operating in a fast-paced, ambiguous environment while managing multiple priorities and driving workplans proactively 10+ years of experience in software engineering, technology architecture, and end-to-end innovative solution delivery Desired Qualifications: Experience building innovative digital products in a regulated environment (financial services preferred) with strong security and risk-awareness Experience deploying AI solutions in highly controlled environments using technologies or patterns such as VPC Service Controls (VPC-SC), private networking, DLP, and secure service-to-service communication Strong API design skills, integration patterns, and experience building services that can be reused across multiple use cases Experience deploying agentic and AI-enabled applications using Google Cloud Run or comparable cloud-native container platforms Experience implementing grounding/RAG solutions using Vertex AI Search / Discovery Engine or comparable enterprise retrieval technologies Experience implementing AI safety and security controls using Model Armor or comparable technologies Experience managing token usage, model consumption, observability, and AI-related cost governance Experience with modern front-end frameworks and rapid prototyping approaches (e.g., React/Next.js or equivalent), plus strong backend development depth Strong hands-on software engineering experience using one or more modern programming languages (e.g., Java, Python, TypeScript/JavaScript, or similar), with the ability to rapidly learn and apply new technologies as needed Demonstrated success creating reusable accelerators, including templates, libraries, reference implementations, AI patterns, and governance frameworks that scale delivery across teams Experience with AWS Bedrock, Azure OpenAI, or comparable AI platforms is beneficial when combined with demonstrated hands-on Google Cloud AI deployment experience Strong communication skills with the ability to explain architecture decisions, tradeoffs, and outcomes to technical and non-technical audiences Experience building with a product-centric mindset and ability to iteratively delivery; ability to create momentum while maintaining engineering discipline Only candidates available and ready to work directly as Genesis10 employees will be considered for this position. If you have the described qualifications and are interested in this exciting opportunity, please apply! Ranked a Top Staffing Firm in the U.S. by Staffing Industry Analysts for six consecutive years, Genesis10 puts thousands of consultants and employees to work across the United States every year in contract, contract-for-hire, and permanent placement roles. With more than 300 active clients, Genesis10 provides access to many of the Fortune 100 firms and a variety of mid-market organizations across the full spectrum of industry verticals. For contract roles, Genesis10 offers the benefits listed below. If this is a perm-placement opportunity, our recruiter can talk you through the unique benefits offered for that particular client. Benefits of Working with Genesis10: Access to hundreds of clients, most who have been working with Genesis10 for 5-20+ years The opportunity to have a career-home in Genesis10; many of our consultants have been working exclusively with Genesis10 for years Access to an experienced, caring recruiting team (more than 7 years of experience, on average) Behavioral Health Platform Medical, Dental, Vision Health Savings Account Voluntary Hospital Indemnity (Critical Illness & Accident) Voluntary Term Life Insurance 401K Sick Pay (for applicable states/municipalities) Commuter Benefits (Dallas, NYC, SF, and Illinois) For multiple years running, Genesis10 has been recognized as a Top Staffing Firm in the U.S., as a Best Company for Work-Life Balance . click apply for full job details

The Annapurna Labs team at Amazon Web Services (AWS) builds AWS Neuron, the software development kit used to accelerate deep learning and GenAI workloads on Amazon's custom machine learning accelerators, Inferentia and Trainium. The AWS Neuron SDK, developed by the Annapurna Labs team at AWS, is the backbone for accelerating deep learning and GenAI workloads on Amazon's Inferentia and Trainium ML accelerators. This comprehensive toolkit includes an ML compiler, runtime, and application framework that seamlessly integrates with popular ML frameworks like PyTorch and JAX enabling unparalleled ML inference and training performance. The Inference Enablement and Acceleration team is at the forefront of running a wide range of models and supporting novel architecture alongside maximizing their performance for AWS's custom ML accelerators. Working across the stack from PyTorch till the hardware-software boundary, our engineers build systematic infrastructure, innovate new methods and create high-performance kernels for ML functions, ensuring every compute unit is fine tuned for optimal performance for our customers' demanding workloads. We combine deep hardware knowledge with ML expertise to push the boundaries of what's possible in AI acceleration. As part of the broader Neuron organization, our team works across multiple technology layers - from frameworks and kernels and collaborate with compiler to runtime and collectives. We not only optimize current performance but also contribute to future architecture designs, working closely with customers to enable their models and ensure optimal performance. This role offers a unique opportunity to work at the intersection of machine learning, high-performance computing, and distributed architectures, where you'll help shape the future of AI acceleration technology You will architect and implement business critical features, and mentor a brilliant team of experienced engineers. We operate in spaces that are very large, yet our teams remain small and agile. There is no blueprint. We're inventing. We're experimenting. It is a very unique learning culture. The team works closely with customers on their model enablement, providing direct support and optimization expertise to ensure their machine learning workloads achieve optimal performance on AWS ML accelerators. The team collaborates with open source ecosystems to provide seamless integration and bring peak performance at scale for customers and developers. This role is responsible for development, enablement and performance tuning of a wide variety of LLM model families, including massive scale large language models like the Llama family, DeepSeek and beyond. The Inference Enablement and Acceleration team works side by side with compiler engineers and runtime engineers to create, build and tune distributed inference solutions with Trainium and Inferentia. Experience optimizing inference performance for both latency and throughput on such large models across the stack from system level optimizations through to Pytorch or JAX is a must have. You can learn more about Neuron Key job responsibilities This role will help lead the efforts in building distributed inference support for Pytorch in the Neuron SDK. This role will tune these models to ensure highest performance and maximize the efficiency of them running on the customer AWS Trainium and Inferentia silicon and servers. Strong software development using Python, System level programming and ML knowledge are both critical to this role. Our engineers collaborate across compiler, runtime, framework, and hardware teams to optimize machine learning workloads for our global customer base. Working at the intersection of software, hardware, and machine learning systems, you'll bring expertise in low-level optimization, system architecture, and ML model acceleration. In this role, you will: Design, develop, and optimize machine learning models and frameworks for deployment on custom ML hardware accelerators. Participate in all stages of the ML system development lifecycle including distributed computing based architecture design, implementation, performance profiling, hardware-specific optimizations, testing and production deployment. Build infrastructure to systematically analyze and onboard multiple models with diverse architecture. Design and implement high-performance kernels and features for ML operations, leveraging the Neuron architecture and programming models Analyze and optimize system-level performance across multiple generations of Neuron hardware Conduct detailed performance analysis using profiling tools to identify and resolve bottlenecks Implement optimizations such as fusion, sharding, tiling, and scheduling Conduct comprehensive testing, including unit and end-to-end model testing with continuous deployment and releases through pipelines. Work directly with customers to enable and optimize their ML models on AWS accelerators Collaborate across teams to develop innovative optimization techniques A day in the life You will collaborate with a cross-functional team of applied scientists, system engineers, and product managers to deliver state-of-the-art inference capabilities for Generative AI applications. Your work will involve debugging performance issues, optimizing memory usage, and shaping the future of Neuron's inference stack across Amazon and the Open Source Community. As you design and code solutions to help our team drive efficiencies in software architecture, you'll create metrics, implement automation and other improvements, and resolve the root cause of software defects. You will also build high-impact solutions to deliver to our large customer base and participate in design discussions, code review, and communicate with internal and external stakeholders. You will work cross-functionally to help drive business decisions with your technical input. You will work in a startup-like development environment, where you're always working on the most important initiative. About the team The Inference Enablement and Acceleration team fosters a builder's culture where experimentation is encouraged, and impact is measurable. We emphasize collaboration, technical ownership, and continuous learning. Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we're building an environment that celebrates knowledge-sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects that help our team members develop your engineering expertise so you feel empowered to take on more complex tasks in the future. Join us to solve some of the most interesting and impactful infrastructure challenges in AI/ML today. BASIC QUALIFICATIONS - Bachelor's degree in computer science or equivalent - 3+ years of non-internship professional software development experience - 3+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience - Fundamentals of Machine learning and LLMs, their architecture, training and inference lifecycles along with work experience on some optimizations for improving the model execution. - Software development experience in C++, Python (experience in at least one language is required). - Strong understanding of system performance, memory management, and parallel computing principles. - Proficiency in debugging, profiling, and implementing best software engineering practices in large-scale systems. PREFERRED QUALIFICATIONS - Familiarity with PyTorch, JIT compilation, and AOT tracing. - Familiarity with CUDA kernels or equivalent ML or low-level kernels - Candidates with performant kernel development such as CUTLASS, FlashInfer etc., would be well suited. - Familiar with syntax and tile-level semantics similar to Triton. - Experience with online/offline inference serving with vLLM, SGLang, TensorRT or similar platforms in production environments. - Deep understanding of computer architecture, operation systems level software and working knowledge of parallel computing. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company's reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. Our inclusive culture empowers Amazonians to deliver the best results for our customers . click apply for full job details

Job Description Job Description Founded in 2012, H2O.ai is on a mission to democratize AI. As the world's leading agentic AI company, H2O.ai converges Generative and Predictive AI to help enterprises and public sector agencies develop purpose-built GenAI applications on their private data. With a focus on Sovereign AI-secure, compliant, and infrastructure-flexible deployments-H2O.ai delivers solutions that align with the highest standards of data privacy and control. Our open-source technology is trusted by over 20,000 organizations worldwide, including more than half of the Fortune 500. H2O.ai powers AI transformation for companies like AT&T, Commonwealth Bank of Australia, Chipotle, Workday, Progressive Insurance, and NIH. H2O.ai partners include NVIDIA, Dell Technologies, Deloitte, Ernst & Young (EY), Snowflake, AWS, Google Cloud Platform (GCP), VAST Data and MinIO. H2O.ai's AI for Good program supports nonprofit groups, foundations, and communities in advancing education, healthcare, and environmental conservation. With a vibrant community of 2 million data scientists worldwide, H2O.ai aims to co-create valuable AI applications for all users. H2O.ai has raised 256 million from investors, including Commonwealth Bank, NVIDIA, Goldman Sachs, Wells Fargo, Capital One, Nexus Ventures and New York Life. For more information, visit . About This Opportunity We are looking for a Principal AI Engineer who builds things that matter. You will design and ship end-to-end AI solutions for some of APAC's most complex enterprise problems - spanning agentic AI systems, LLM applications, and production ML pipelines. This is a hands-on engineering role embedded within a customer-facing field team, meaning your work will be seen, used, and evaluated by real enterprises from day one. You will work alongside Kaggle Grandmasters, ML engineers, and domain experts to deliver AI that goes beyond demos - into production, into workflows, and into measurable business outcomes. This position is based in Dallas, Texas and requires onsite customer interfacing. What You Will Do Customer Engagement Leadership Lead end-to-end technical engagement with enterprise customers, acting as the senior point of accountability for delivery quality, stakeholder relationships, and outcomes. Manage multiple concurrent engagement streams simultaneously - coordinating workplans, resourcing, and milestones across cross-functional teams. Serve as the primary technical escalation point for customer issues, proactively identifying risks and driving resolution across engineering, product, and leadership. Build and maintain trusted relationships with customer data science teams, engineering leads, and executive stakeholders - translating business needs into technical direction and back again. Lead pre-sales and proof-of-concept engagements, setting the technical strategy and ensuring the team delivers demonstrations that build genuine enterprise trust. Represent H2O.ai externally at customer workshops, executive briefings, and technical deep-dives as a credible senior voice. Agentic AI & LLM Engineering Design and build agentic AI systems and multi-agent frameworks that automate complex, multi-step enterprise workflows. Develop and deploy LLM-powered applications using RAG, fine-tuning, prompt engineering, function calling, and tool use. Implement guardrails, evaluation frameworks, and responsible AI controls to ensure production-grade reliability and safety. Stay current with the rapidly evolving agentic AI landscape - MCP, LLM orchestration frameworks, reasoning models - and bring the best into customer engagements. End-to-End AI Application Development Own the full development lifecycle across multiple streams: from problem framing and data exploration through model development, API integration, and production deployment. Build scalable backend services and APIs that expose AI capabilities to enterprise applications and workflows. Integrate AI models into customer environments - cloud, on-prem, and hybrid - ensuring performance, stability, and maintainability at scale. Develop ML pipelines and LLMOps infrastructure that support continuous model improvement and monitoring in production. Team Collaboration & Delivery Excellence Coordinate delivery across engineers, program managers, and solution architects - ensuring workstreams are aligned, unblocked, and progressing to plan. Set the technical bar for the engagements you lead, reviewing outputs, shaping architecture decisions, and ensuring engineering quality across the team. Mentor and guide junior ML engineers and solution engineers within engagements, building team capability alongside delivery. Collaborate closely with H2O.ai product and engineering teams to surface customer feedback, shape roadmap input, and resolve platform-level issues. What We Are Looking For Experience & Background 8+ years of hands-on AI/ML engineering experience, including end-to-end model development and production deployment. Demonstrable experience leading technical delivery across complex, multi-stakeholder enterprise engagements - not just executing within them. Demonstrable experience building LLM-powered applications - RAG pipelines, agentic workflows, fine-tuned models, or similar. Strong Python engineering skills; experience with ML frameworks (PyTorch, TensorFlow, scikit-learn) and LLM tooling (LangChain, LlamaIndex, or equivalent). Experience deploying AI services in cloud or enterprise environments (AWS, Azure, GCP, on-prem Kubernetes). Skills & Capabilities Proven ability to manage multiple concurrent workstreams and coordinate cross-functional teams toward shared delivery milestones. Deep understanding of modern GenAI concepts: prompt engineering, RAG, fine-tuning, RLHF, model evaluation, guardrails, and LLMOps. Solid grounding in classical ML - able to select the right tool for the problem, not just default to the latest LLM. Backend development skills: REST APIs, containerisation (Docker/Kubernetes), and CI/CD pipelines for AI applications. Strong executive communication - able to run a board-level briefing one hour and a technical design review the next, credibly. Comfortable with ambiguity and able to set direction for a team when requirements are incomplete or evolving. How to Stand Out From the Crowd Kaggle or competitive ML experience. Familiarity with H2O.ai products, Wave, or H2O Document AI. Experience in financial services, healthcare, or other regulated industry AI deployments. Exposure to tabular foundation models, AutoML, or enterprise ML platforms. Prior experience in a customer-facing or field engineering role. Why H2O.ai? Market leader in total rewards Remote-friendly culture Flexible working environment Be part of a world-class team Career growth H2O.ai is committed to creating a diverse and inclusive culture. All qualified applicants will receive consideration for employment without regard to their race, ethnicity, religion, gender, sexual orientation, age, disability status or any other legally protected basis. H2O.ai is an innovative AI cloud platform company, leading the mission to democratize AI for everyone. Thousands of organizations from all over the world have used our cutting-edge technology across a variety of industries. We've made it easy for people at all levels to generate breakthrough solutions to complex business problems and advance the discovery of new ideas and revenue streams. We push the boundaries of what is possible with artificial intelligence. H2O.ai employs the world's top Kaggle Grandmasters, the community of best-in-the-world machine learning practitioners and data scientists. A strong AI for Good ethos and responsible AI drive the company's purpose. Please visit

Senior Lead AI Engineer (GenAI Platform Services) 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 - along with our deep experience in machine learning - 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 & 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: 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. 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. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. The Ideal Candidate: 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. Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production. 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. 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. You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown. Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 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 4 years of experience developing AI and ML algorithms or technologies At least 6 years of experience programming with Python, Go, Scala, or Java Preferred Qualifications: 7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, integrating, delivering, and supporting complex AI systems Demonstrated ability to lead and mentor an engineering team and influence cross-functional stakeholders 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 Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers 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: $229,900 - $262,400 for Sr. Lead AI Engineer McLean, VA: $229,900 - $262,400 for Sr. Lead AI Engineer New York, NY: $250,800 - $286,200 for Sr. Lead AI Engineer San Jose, CA: $250,800 - $286,200 for Sr. 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'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 ; New York City's Fair Chance Act; Philadelphia'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- or via email at . 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 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).