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data ai engineer

The Carlyle Group

<div>
 
 
 Company Profile
 
 
 
 The Carlyle Group (NASDAQ: CG) is a global investment firm with $475 billion of assets under management, across 678 investment vehicles as of March 31, 2026. Founded in 1987 in Washington, DC, Carlyle has grown into one of the world's largest and most successful investment firms, with more than 2,500 professionals operating in 28 offices in North America, Europe, the Middle East, Asia and Australia.
 
 
 
 
 
 Carlyle's purpose is to connect people, ideas, and capital to fuel growth for companies and performance for investors, which range from public and private pension funds to wealthy individuals and families to sovereign wealth funds, unions and corporations. Carlyle invests across three segments - Global Private Equity, Global Credit and Carlyle AlpInvest - and has deep expertise across industries, markets, and geographies.
 
 
 
 
 
 At Carlyle, we believe that a wide spectrum of experiences and viewpoints drives performance and success. Our CEO, Harvey Schwartz, has stated that, "To build better businesses and create value for all of our stakeholders, we are focused on assembling leadership teams with the strongest insights from a range of perspectives." Reflecting this view, emphasis is placed on development, retention and inclusion through our internal processes and seven Employee Resource Groups (ERGs). We cultivate a culture where ideas are openly shared and challenged, connecting diverse expertise and perspectives to drive enduring value.
 
 
 
 
 
 
 Fund or Department Description
 
 
 
 The Data &amp; AI Engineer sits within Carlyle's Enterprise Technology &amp; Data organization and supports firm-wide data and AI initiatives spanning investment platforms, portfolio operations, investor relations, and corporate functions. The role operates within a federated data operating model, partnering with domain engineering teams to implement shared platforms and reusable patterns for data and AI under the technical direction of the Senior AI &amp; Data Architect.
 
 
 
 
 
 
 Position Summary
 
 
 
 The Data &amp; AI Engineer is an experienced, hands-on engineer who turns Carlyle's data and AI architecture into working production systems. Reporting to the Senior AI &amp; Data Architect, this role is responsible for building and operating the pipelines, semantic layers, retrieval systems, and AI-ready data products that power analytics, automation, LLMs, agents, and generative AI applications across the firm.
 
 
 
 
 
 The role requires deep, hands-on expertise across modern data engineering and applied AI engineering. The Data &amp; AI Engineer will implement retrieval-augmented generation (RAG) patterns, embedding and indexing pipelines, vector stores, and semantic models alongside core ELT, streaming, and analytical pipelines - treating LLMs, agents, and copilots as first-class consumers of the data platform.
 
 
 
 
 
 This is a senior individual-contributor engineering role that executes against architectural standards, contributes to their evolution through hands-on learning, and partners closely with data science, AI engineering, governance, and domain teams to deliver trusted, AI-consumable data at enterprise scale.
 
 
 
 
 
 
 What Success Looks Like:
 
 In the first 12 months, this role will deliver foundational AI-ready data pipelines and retrieval components defined in the target-state architecture, productionize one or more priority RAG or agent-grounding use cases, and establish reusable engineering patterns that other domain teams can adopt across the federated data platform.
 
 
 
 
 
 
 In-office requirement:
 
 4 days per week
 
 
 
 
 
 
 Primary Responsibilities:
 
 
 
 
 AI Data Pipelines &amp; Retrieval Systems (&asymp;35%)
 
 
 <ul>
 <li>
 Build and operate AI-ready data pipelines - embedding generation, chunking, indexing, and refresh workflows - that make Carlyle's enterprise data reliably retrievable by LLMs, agents, and generative AI applications.
 </li>
 <li>
 Implement retrieval-augmented generation (RAG) components, including vector store integrations, hybrid search, re-ranking, and grounding logic, against architectural patterns defined by the Senior AI &amp; Data Architect.
 </li>
 <li>
 Develop and maintain tool and function interfaces that allow agents and copilots to query and act on enterprise data safely, with appropriate guardrails, logging, and evaluation hooks.
 </li>
 <li>
 Partner with Data Science and AI Engineering teams to operationalize feature stores, evaluation datasets, and reusable AI data products.
 </li>
 <li>
 Contribute to semantic and context engineering work that powers natural-language analytics, conversational reporting, and AI-driven insights for business users.
 </li>
 </ul>
 
 
 
 
 
 Modern Data Pipeline Engineering (&asymp;30%)
 
 
 <ul>
 <li>
 Design, build, and maintain production-grade ELT, streaming, and transformation pipelines using tools such as dbt, Fivetran and Snowflake.
 </li>
 <li>
 Implement ingestion, modeling, and consumption patterns that meet enterprise standards for scalability, performance, security, resiliency, and cost efficiency.
 </li>
 <li>
 Write clean, well-tested Python and SQL; apply software engineering best practices including version control, code review, CI/CD, modular design, and automated testing.
 </li>
 <li>
 Productionize new sources and domains under the federated operating model, partnering with domain data engineers to apply shared platform capabilities consistently.
 </li>
 </ul>
 
 
 
 
 
 Semantic Layer &amp; Data Product Development (&asymp;20%)
 
 
 <ul>
 <li>
 Implement semantic models, data contracts, and analytical/dimensional models that enable trusted self-service analytics and reliable AI grounding.
 </li>
 <li>
 Build and maintain reusable data products with clear ownership, documented contracts, and contextual metadata suitable for both human and AI consumers.
 </li>
 <li>
 Collaborate with the Senior AI &amp; Data Architect to refine and extend enterprise semantic standards based on what works in production.
 </li>
 <li>
 Support discovery and consumption tooling so that analysts, applications, and agents can find and use data products with minimal friction.
 </li>
 </ul>
 
 
 
 
 
 Data Quality, Observability &amp; AI Trust (&asymp;10%)
 
 
 <ul>
 <li>
 Implement data quality checks, lineage capture, and pipeline observability across both data and AI workloads.
 </li>
 <li>
 Build logging, evaluation, and monitoring components for AI systems - including prompt and response capture, retrieval metrics, and model performance signals - in line with governance standards.
 </li>
 <li>
 Partner with Data Governance to operationalize metadata, stewardship, and access controls, ensuring AI systems consume enterprise data with the same rigor as human users.
 </li>
 <li>
 Surface issues early, propose remediations, and feed lessons learned back into architectural patterns.
 </li>
 </ul>
 
 
 
 
 
 Collaboration &amp; Engineering Craft (&asymp;5%)
 
 
 <ul>
 <li>
 Participate in architectural design reviews and contribute hands-on engineering perspective to evolving patterns and standards.
 </li>
 <li>
 Mentor junior data engineers and analysts on modern data and AI engineering practices.
 </li>
 <li>
 Document patterns, write runbooks, and share knowledge across the federated organization to accelerate adoption of reusable platform capabilities.
 </li>
 </ul>
 
 
 
 
 
 Requirements:
 
 
 
 
 Education &amp; Certifications
 
 
 <ul>
 <li>
 Bachelor's degree, required
 </li>
 <li>
 Concentration in computer science, data engineering, information systems, or a related field, preferred
 </li>
 <li>
 Masters degree, preferred
 </li>
 <li>
 Relevant certifications in cloud, data engineering, analytics, or AI/ML are preferred
 </li>
 </ul>
 
 
 
 
 
 Professional Experience
 
 
 <ul>
 <li>
 6+ years of overall relevant technical experience, required
 </li>
 <li>
 Experience in data engineering, analytics engineering, or platform engineering, with at least 1-2 years of direct, hands-on experience building generative AI or AI/ML systems in production.
 </li>
 <li>
 Proven experience implementing retrieval, grounding, and semantic components for LLM- or agent-based applications, including RAG pipelines, vector stores, embedding workflows, and structured tool use.
 </li>
 <li>
 Hands-on experience with one or more modern AI platforms and tooling categories (e.g., AWS Bedrock, Databricks ML, Snowflake Cortex, OpenAI/Anthropic APIs, LangChain/LlamaIndex or equivalents, MLflow, and vector databases such as Databricks Vector Search, pgvector, or Pinecone).
 </li>
 <li>
 Strong, demonstrable expertise in Python and SQL, with working knowledge of distributed processing frameworks (e.g., Spark).
 </li>
 <li>
 Deep, hands-on experience with modern data stacks - dbt, Fivetran, Snowflake - in AWS-based environments.
 </li>
 <li>
 Track record of building data pipelines and products whose consumers include AI systems, not only BI tools and human analysts.
 </li>
 <li>
 Palantir experience a plus.
 </li>
 <li>
 Experience operating within federated data operating models and complex, regulated enterprise environments; financial services experience preferred.
 </li>
 </ul>
 
 
 
 
 
 Competencies &amp; Attributes
 
 
 <ul>
 <li>
 Demonstrated AI-forward instinct: defaults to asking how AI changes what gets built, rather than whether AI can be added later.
 </li>
 <li>
 Fluency in current AI engineering patterns (RAG, agents, tool use, evaluations, guardrails, observability) and the practical trade-offs involved in shipping them.
 </li>
 <li>
 Strong engineering craft: clean code, automated testing, thoughtful design, and a bias toward production-quality systems over prototypes.
 </li>
 <li>
 Pragmatic, delivery-oriented mindset with strong attention to data quality, AI trust, and long-term maintainability; able to distinguish durable engineering decisions from AI hype.
 </li>
 <li>
 Collaborative partner to architects, data scientists, AI engineers, and domain teams; comfortable operating in a matrixed, federated organization and in high-visibility transformational initiatives.
 </li>
 </ul>
 
 
 
 
 
 Benefits/Compensation
 
 
 
 The compensation range for this role is specific to the applicable office location and takes into account a wide range of factors, including required and preferred skill sets; prior experience and training; and licenses and/or certifications.
 
 
 
 
 
 The anticipated base salary range for this role is $160,000 to $180,000.
 
 
 
 
 
 In addition to base salary, the hired professional will receive a comprehensive benefits package including retirement benefits, health insurance, life and disability insurance, paid time off, paid holidays, family planning benefits, and wellness programs. The hired professional may also be eligible for an annual discretionary incentive program based on individual and organizational performance.
 
</div>

Data & AI Engineer

Traversal

<div><h3 class="jobSectionHeader">About Traversal</h3>
Traversal is the AI Site Reliability Engineer (SRE) for the enterprise&mdash;already trusted by some of the largest companies in the world to troubleshoot, remediate, and even prevent the most complex production incidents. Our mission is to free engineers from endless firefighting and enable them to focus on creative, high-impact work.
Our roots remain deeply embedded in AI research, and we&rsquo;re channeling that scientific rigor and creativity into building the premier AI agent lab for the enterprise. Hence, what we&rsquo;re proudest of is assembling the most talented yet nicest group of individuals, including researchers from MIT, Harvard, and Berkeley, to world-class engineers from industry: Citadel Securities, Cockroach Labs, Datadog, DE Shaw, ServiceNow, Glean, Perplexity, Pinecone, and more, to take on one of the hardest problems for AI to solve. Without the entire team, none of this would be possible.<h3 class="jobSectionHeader">
The Role</h3>
As a Product Engineer at Traversal, you&rsquo;ll play a key role in designing and building core features powered by our AI site reliability engineer. From the user interface to the backend and infrastructure, you&rsquo;ll develop product components to enable real-time incident detection, root cause analysis, and automated remediation in some of the most complex production environments. This role will focus on the ability to work across the full pipeline of our product, and someone who can have a strong product sense while also being comfortable working around AI and data processing infrastructure will be the best fit.<h3 class="jobSectionHeader">
Responsibilities</h3><ul><li>
Product Impact: Translate AI-powered insights into user-friendly features that empower engineers and reduce cognitive load.</li><li>
User Experience: Innovate and drive the evolution of UX/UI design, rapidly iterating based on user feedback to improve overall usability.</li><li>
Agent Development: Build AI agents with a mind for user-experience and capabilities like long-horizon work, proactiveness, readability, and evidence citation.</li><li>
API Development: Design and implement high-performance APIs to enable seamless communication between backend systems and frontend interfaces.</li><li>
Data Management: Ensure efficient data storage, retrieval, and processing, leveraging technologies like PostgreSQL, Redis, or others.</li><li>
AI Integration: Collaborate with AI engineers/researchers to integrate AI-driven insights and solutions into backend systems, and take ownership of API authentication and authorization frameworks.</li><li>
Data Visualization: Develop intuitive interfaces for presenting and interacting with complex time-series and topological data.</li></ul><h3 class="jobSectionHeader">
Requirements</h3><ul><li>
4+ years of software engineering experience, with a strong focus on full-stack systems.</li><li>
Proven ability to lead in fast-paced startup environments, with limited resources, shifting priorities, and minimal structure.</li><li>
Strong experience with Python and web frameworks such as FastAPI.</li><li>
Hands-on experience with React, TypeScript, Next.js, and TailwindCSS to build fast, responsive, and maintainable frontends.</li><li>
Experience deploying applications on AWS, working with ECS or Kubernetes, Postgres for data storage, and S3 for large-scale object storage.</li><li>
Note: You don&rsquo;t need to meet every single requirement. If you have deep experience in a subset of these areas, we encourage you to apply.</li></ul><h3 class="jobSectionHeader">
Nice to Have</h3><ul><li>
Familiarity with Python-based ecosystems is a plus.</li><li>
Experience working with Agentic AI systems or in the observability domain.</li><li>
Background in large-scale, complex, data-driven applications.</li><li>
Familiarity with building AI or LLM-powered products.</li></ul><h3 class="jobSectionHeader">
Compensation</h3>
We offer competitive compensation, startup equity, health insurance, and additional benefits. The U.S. base salary range for this full-time, in-person role in New York is $150,000&ndash;$300,000, plus equity and benefits. Our salary ranges are based on location, level, and role. Individual compensation is determined by experience, skills, and job-related knowledge.<h3 class="jobSectionHeader">
Why You Should Join Us</h3>
We&rsquo;ll make sure you&rsquo;re fully supported with health insurance, a great tech setup, flexible time off, and plenty of in-office snacks. We offer competitive salary and equity packages, and take thoughtful consideration with every hire on our small, high-impact team.
Traversal is fully in-office, 5 days a week, based in New York near Madison Square Park. We have a collaborative, hard-working culture and are energized by building the future of AI-powered software maintenance.
Working here means owning meaningful parts of the product, having the flexibility to move fast, and learning constantly. This is a place to grow your career, make a real impact, and help define a new category of infrastructure software.</div>

Product Engineer

Prolific

<div>
 
 AI Trainer &ndash; Machine Learning Specialists
 
 
 
 
 About Prolific
 
 
 
 Prolific is not just another player in the AI space &ndash; we are building the biggest pool of quality human data in the world.
 
 
 Over 35,000 AI developers, researchers, and organizations use Prolific to gather data from paid study participants with a wide variety of experiences, knowledge, and skills.
 
 
 
 The role
 
 
 
 We&rsquo;re looking for
 
 AI Trainer &ndash; Machine Learning Specialists
 
 to help train and evaluate cutting-edge AI models using real ML expertise. If you have the necessary experience, we&rsquo;ll send you a quick
 
 10- to 15-minute test
 
 to assess your skills and suitability for AI tasks. If successful, you&rsquo;ll be invited to join Prolific as a participant, where you&rsquo;ll get paid to train and evaluate powerful AI models.
 
 
 Researchers looking for your skills tend to pay up to
 
 $150/hr per AI task completed
 
 . You must be prepared to complete paid tasks that require
 
 one hour of uninterrupted work
 
 , though many are shorter.
 
 
 What you&rsquo;ll bring
 
 
 <ul>
 <li>
 AI Training task skills and verifiable professional experience as a Machine Learning Specialist (e.g., ML engineer, data scientist, applied scientist, research engineer)
 </li>
 <li>
 A willingness to take our skills verification test to assess your suitability for our participant pool
 </li>
 <li>
 Strong attention to detail and the ability to concentrate on complex tasks for up to one hour at a time
 </li>
 <li>
 A reliable and fast internet connection and access to a computer
 </li>
 <li>
 A willingness to self-declare your earnings, as our participants are self-employed
 </li>
 <li>
 A Paypal account to receive payment from our clients
 
 
 </li>
 </ul>
 
 What you&rsquo;ll be doing in the role
 
 
 
 <ul>
 <li>
 Completing AI training tasks such as analyzing, editing, and writing annotations (including technical reasoning and structured evaluation)
 </li>
 <li>
 Judging the performance of AI in performing ML-relevant tasks (e.g., model/experiment critique, data leakage detection, metrics interpretation, debugging approach, methodology review)
 </li>
 <li>
 Improving cutting-edge AI models by providing expert feedback on correctness, robustness, clarity, and technical depth
 
 
 </li>
 </ul>
 
 Key Technologies
 
 
 
 <ul>
 <li>
 General AI Training
 </li>
 <li>
 Model Evaluation and Evals
 </li>
 <li>
 Trust and Safety
 </li>
 <li>
 Red Teaming
 </li>
 <li>
 Quality Analytics
 </li>
 <li>
 Data/ML Concepts (e.g., supervised learning, deep learning, NLP, CV, statistics, experimentation)
 
 
 </li>
 </ul>
 
 Why Prolific is a great platform to join as a Participant
 
 
 
 Joining our platform as a Prolific participant will give you the chance to influence the AI models of the future using professional machine learning expertise. Once you pass our assessment, you can join Prolific in just 15 minutes, and start enjoying competitive pay rates, flexible hours, and the ability to work from home.
 
 
 We've built a unique platform that connects researchers and companies with a global pool of participants, enabling the collection of high-quality, ethically sourced human behavioural data and feedback. This data is the cornerstone of developing more accurate, nuanced, and aligned AI systems.
 
 
 We believe that the next leap in AI capabilities won't come solely from scaling existing models, but from integrating diverse human perspectives and behaviours into AI development. By providing this crucial human data infrastructure, Prolific is positioning itself at the forefront of the next wave of AI innovation &ndash; one that reflects the breath and the best of humanity.
 
 
 
 Links to more information on Prolific
 
 
 
 Website
 
 
 Youtube
 
 
 Privacy Statement
 
 
 By submitting your application, you agree that Prolific may collect your personal data for recruiting and global organisation planning. Prolific's Candidate Privacy Notice explains what personal information Prolific may process, where Prolific may process your personal information, its purposes for processing your personal information, and the rights you can exercise over Prolific use of your personal personal information.
</div>

AI Training - Machine Learning Specialist (EST)

Inherent Technologies

<div>
 
 Job Description
 
 
 
 Seeking a
 
 hands-on AI Engineer/Developer
 
 to rapidly prototype and deliver AI-driven solutions across investment, research, and trading functions. This role is ideal for someone who can bridge
 
 financial domain knowledge with applied AI/ML development
 
 , building proof-of-concepts that can evolve into production-grade tools supporting investment decision-making.
 
 
 
 Key Responsibilities
 
 
 
 Design and develop
 
 AI/ML prototypes
 
 using Python to support investment research, portfolio analytics, and trading insights
 
 
 Build and test
 
 LLM-based and data-driven use cases
 
 (e.g., research summarization, signal generation, document analysis, automation)
 
 
 Work closely with
 
 investment professionals, research teams, and data engineers
 
 to translate business needs into functional AI solutions
 
 
 Develop and integrate
 
 data pipelines, APIs, and analytical models
 
 to support rapid experimentation
 
 
 Leverage tools such as
 
 Jupyter, Pandas, NumPy, LangChain, and cloud AI services (AWS/Azure/OpenAI)
 
 
 
 Perform
 
 data exploration, feature engineering, and model validation
 
 on financial datasets
 
 
 Iterate quickly on prototypes, incorporating feedback to refine models and outputs
 
 
 Ensure solutions consider
 
 data security, governance, and compliance
 
 within a financial services environment
 
 
 
 Required Qualifications
 
 
 
 10+ years of experience in
 
 Python development
 
 with strong hands-on coding ability
 
 
 Experience building
 
 AI/ML or LLM-based applications and prototypes
 
 
 
 Exposure to
 
 financial services, asset management, trading, or investment research
 
 
 
 Strong experience with
 
 data analysis libraries
 
 (Pandas, NumPy) and working with structured/unstructured data
 
 
 Familiarity with
 
 APIs, microservices, and cloud platforms (AWS, Azure, or GCP)
 
 
 
 Ability to work in a
 
 fast-paced, iterative environment
 
 with direct interaction with business stakeholders
 
 
 
 Preferred Qualifications
 
 
 
 Experience with
 
 LLM frameworks
 
 (LangChain, RAG architectures, vector databases)
 
 
 Knowledge of
 
 financial data sets, market data, or portfolio analytics
 
 
 
 Experience prototyping tools for
 
 quant research, credit analysis, or trading workflows
 
 
 
 Familiarity with
 
 Snowflake, Databricks, or modern data platforms
 
 
 
 
 What Success Looks Like
 
 
 
 Rapid delivery of
 
 high-impact AI prototypes
 
 that demonstrate clear business value
 
 
 Strong collaboration with front-office teams to
 
 solve real investment and research problems
 
 
 
 Ability to evolve prototypes into scalable solutions in partnership with engineering teams
</div>

Python Developer/AI Engineer

Amazon Web Services

<div><h2 class="jobSectionHeader">DESCRIPTION</h2><div>
Join Amazon's Data Integration organization and help shape the future of AI-driven data integration! We're seeking a talented Software Engineer to join our AI and Platform Excellence (APEX) team. APEX is at the forefront of leveraging AI/ML to revolutionize data integration workflows, making them simpler, and more efficient. 
 
As a member of APEX, you'll build core algorithms that harness the power of AI and machine learning to simplify the authoring, troubleshooting, upgrading, and optimization of data integration workflows. Your work will directly impact Amazon's ability to manage and utilize vast amounts of data across its many products and services. 
 
Utility Computing (UC) 
AWS Utility Computing (UC) provides product innovations &mdash; from foundational services such as Amazon&rsquo;s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS&rsquo;s services and features apart in the industry. As a member of the UC organization, you&rsquo;ll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for customers who require specialized security solutions for their cloud services. 
 
Key job responsibilities 
<ul><li>Design, develop, and implement AI/ML-powered products for data integration workflows which simplifies complexity in data processing.</li><li>Build and own critical infrastructure powering Amazon's next-generation AI capabilities</li><li>Collaborate with data scientists and ML experts to s to transform innovative ideas into production systems</li><li>Optimize existing algorithms and systems for performance, scalability, and reliability</li><li>Contribute to the full software development lifecycle, from conception to production deployment</li><li>Mentor junior engineers and promote best practices in software development and AI implementation</li></ul> 
A day in the life 
<ul><li>Impact: Your work will directly influence how AI capabilities are developed and deployed at Amazon</li><li>Innovation: Work at the intersection of advanced AI research and enterprise-scale engineering</li><li>Growth: Learn from experts while working with the latest in AI technology</li><li>Purpose: Help shape responsible AI development practices and sustainable computing</li><li>Team: Join a collaborative environment focused on solving complex, meaningful challenges</li></ul> 
This role offers unique exposure to both AI infrastructure and product development, positioning you to make significant contributions to Amazon's AI initiatives while working with some of the industry's brightest minds. 
 
About the team 
AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn&rsquo;t followed a traditional path, or includes alternative experiences, don&rsquo;t let it stop you from applying. 
 
Why AWS? Amazon Web Services (AWS) is the world&rsquo;s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating &mdash; that&rsquo;s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. 
 
Inclusive Team Culture Here at AWS, it&rsquo;s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon conferences, inspire us to never stop embracing our uniqueness. 
 
Mentorship &amp; Career Growth We&rsquo;re continuously raising our performance bar as we strive to become Earth&rsquo;s Best Employer. That&rsquo;s why you&rsquo;ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. 
 
Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there&rsquo;s nothing we can&rsquo;t achieve in the cloud.</div><h2 class="jobSectionHeader"> 
BASIC QUALIFICATIONS</h2><ul><li>3+ years of non-internship professional software development experience</li><li>2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience</li><li>1+ years of software development engineer or related occupational experience</li><li>1+ years of designing and developing large-scale, multi-tiered, multi-threaded, embedded or distributed software applications, tools, systems, and services using: C#, C++, Java, or Perl experience</li><li>1+ years of Object Oriented Design experience</li><li>Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, or a related field</li><li>Experience programming with at least one software programming language</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience</li><li>Bachelor's degree in computer science or equivalent</li></ul> 
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. 
 
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner. 
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life &amp; AD&amp;D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits. 
USA, NY, New York - 158,100.00 - 213,800.00 USD annually</div>

Software Development Engineer, Data Analytics Integration AI and Platform Excellence

Kairon Health

<div><h1 class="jobSectionHeader">About Kairon Health</h1>
Kairon is the execution layer for healthcare. We turn fragmented claims and clinical data into actionable workflows that help ACOs and health networks actually capture their shared savings &mdash; not just measure them after the fact.
We&rsquo;re a seed-stage team of &lt;10, working with real customers managing real patient populations. Our platform spans practice intelligence, care operations, patient activation, and performance analytics. We&rsquo;re AI-native &mdash; not as a buzzword, but because our team builds with Claude, automated transcription, and intelligent workflows as core infrastructure, not bolt-on features.
We&rsquo;re at the stage where our early customers love the product and we need to make onboarding, support, and ongoing operations repeatable without losing the high-touch quality that got us here.<h1 class="jobSectionHeader">
Position Overview</h1>
We&rsquo;re seeking a Senior Product Engineer, Data Applications to own the product layer where data meets decision-making. You&rsquo;ll build the data-powered applications that surface intelligence directly to users &mdash; from the Performance App and ACO-in-a-Box tooling to interactive reporting, scorecards, and next-generation analytics experiences.
This is a full-stack, product-oriented engineering role. You&rsquo;ll design and implement end-to-end solutions (data models, APIs, and UI components) that bring Kairon&rsquo;s insights to life for practice leaders. You&rsquo;ll work closely with engineering leadership, product, and analytics teams to transform complex healthcare data into intuitive, high-impact tools.
You&rsquo;ll thrive here if you&rsquo;re as excited about what you build as why you&rsquo;re building it: an engineer who understands product trade-offs, can shape features from user requirements, and enjoys turning messy data into meaningful, elegant applications.<h1 class="jobSectionHeader">
Key Responsibilities</h1><ul><li>
Own the data-to-application layer: Design, build, and maintain data-driven applications such as performance dashboards, scorecards, and analytic workbenches.</li><li>
Architect end-to-end features: Connect backend models, APIs, and frontend components to deliver interactive insights within the Kairon platform.</li><li>
Collaborate with product and analytics: Translate user needs and clinical/financial metrics into intuitive visualizations and actionable interfaces.</li><li>
Advance in-app intelligence: Integrate data pipelines, LLM insights, and healthcare analytics into user-facing modules (Performance App, ACO-in-a-Box, CRM, and others).</li><li>
Uphold scalability and quality: Design for maintainability, reusability, and performance; implement tests and observability to ensure reliability.</li><li>
Contribute to design &amp; UX: Work with designers to create cohesive, user-friendly experiences that communicate complex data clearly.</li><li>
Champion engineering excellence: Establish best practices, documentation, and component libraries for future applications.</li><li>
Leverage modern AI-assisted tooling: Use LLMs to accelerate development, code review, and refactoring while maintaining rigorous standards.</li></ul><h1 class="jobSectionHeader">
Qualifications</h1><ul><li>
6+ years of professional experience building production web applications (frontend + backend).</li><li>
Strong proficiency in Python, Django/DRF, Vue, and SQL; experience with data visualization frameworks and API design.</li><li>
Experience designing or consuming data models and ETL pipelines (e.g., Snowflake, dbt, or similar).</li><li>
Proven ability to translate product requirements into technical architecture and deliver polished, high-impact user experiences.</li><li>
Familiarity with healthcare, analytics, or enterprise SaaS environments.</li><li>
Clear communication and cross-functional collaboration skills; comfort working directly with product and leadership.</li></ul><h1 class="jobSectionHeader">
Preferred Qualifications</h1><ul><li>
Experience in healthcare or value-based care analytics, EHR data, or claims data models.</li><li>
Prior work integrating LLM-driven insights, AI-based summarization, or contextual intelligence into applications.</li><li>
Strong understanding of data visualization principles and UX for analytics products.</li><li>
Background that spans both engineering and product management (technical PM, full-stack data apps, or similar hybrid roles).</li><li>
Previous experience in an early-stage or high-growth startup environment.</li></ul><h1 class="jobSectionHeader">
Why This Role</h1><ul><li>
Impact. You&rsquo;re not maintaining someone else&rsquo;s machine. You&rsquo;re building customer operations from the ground up at a company where the work directly affects whether patients get better care.</li><li>
Growth. This role has a clear trajectory. Depending on your strengths and interests, this becomes Head of Customer Success, Director of Implementations, or a Product leadership role as we scale. You&rsquo;ll have the context and relationships to grow into whatever the company needs most.</li><li>
Stage. We&rsquo;re past the &ldquo;will this work?&rdquo; phase &mdash; customers are live and getting value. We&rsquo;re in the &ldquo;how do we do this 10x without breaking?&rdquo; phase. That&rsquo;s the most interesting operational puzzle in a startup.</li><li>
Equity. You&rsquo;ll have meaningful ownership as one of our first 10 hires, with a real seat at the table.</li></ul>
Diversity and inclusion are core to our culture. If you are a member of an underrepresented group in tech, we strongly encourage you to apply.
Compensation Range: $170K - $190K</div>

Product Engineer, Data

Rebel Hotel Company

<div>Job Title: AI Engineer
Location: New York, NY
Department: Technology/Revenue Strategy
Reports To: Chief Executive Officer
FLSA Status: Exempt
Work Type: Remote Position with occasional travel to the Corporate Office
Employment Type: Full Time
Company: Rebel Hotel Company
About Rebel Hotel Company: Rebel Hotel Company is one of the fastest-growing third-party hotel management companies in the United States, recognized for delivering bold results, operational excellence, and distinctive guest experiences. We operate a diverse portfolio of full-service, lifestyle, and branded hotels across major metropolitan and resort markets. We are building a culture of leadership, innovation, and accountability&mdash;and we&rsquo;re just getting started.
Position Summary: We're a hospitality company building the next generation of intelligent pricing, demand, and guest-experience systems. Today our commercial teams run rate strategy, RFP negotiations, and account planning on spreadsheets and intuition. We're hiring an AI Engineer to turn that work into software &mdash; models and tools that forecast demand, optimize rates, and surface account intelligence so our revenue managers make sharper decisions, faster.
This is a hands-on engineering role with direct line of sight to revenue. You'll work alongside revenue managers, sales leaders, and data analysts, shipping production systems that touch real pricing and booking decisions across our portfolio.
What You'll Build
<ul><li>Demand forecasting models that predict occupancy and room-night demand by property, segment, day-of-week, and season &mdash; accounting for events, seasonality, and booking pace.</li>
<li>Dynamic pricing and rate-optimization engines that recommend BAR and corporate rates, balancing occupancy, ADR, and RevPAR against competitor positioning.</li>
<li>Account intelligence tooling that ingests internal production data and external signals (M&amp;A activity, headcount trends, travel-budget shifts) to flag growing accounts, at-risk accounts, and uncaptured market opportunity.</li>
<li>Labor and staffing models that forecast labor demand against projected occupancy and arrivals &mdash; optimizing schedules, hours, and cost across housekeeping, front desk, F&amp;B, and other departments while protecting service levels.</li>
<li>RFP and negotiation support tools that help the team price contracts, model rate scenarios, and prioritize target accounts during RFP season.</li>
<li>LLM-powered workflows &mdash; summarizing market intelligence, drafting account strategy notes, and answering natural-language questions over revenue data.</li>
<li>A testing laboratory for beta technologies &mdash; stand up and run a controlled environment where new AI tools and models can be piloted, stress-tested, and validated against real operational data before broader rollout, including the experimentation framework, sandboxed data, and feedback loops with property and commercial teams</li>
</ul>
What You'll Do
<ul><li>Design, train, evaluate, and deploy machine learning models on real booking, rate, and market data.</li>
<li>Build data pipelines that bring together PMS, CRS, booking-channel, and third-party market data into clean, reliable feature sets.</li>
<li>Stand up the infrastructure to serve models in production &mdash; APIs, monitoring, retraining, and guardrails.</li>
<li>Operate the beta testing lab &mdash; design pilots, recruit internal users, measure results, and decide what graduates to production versus what gets killed.</li>
<li>Partner closely with revenue and commercial teams to translate domain knowledge into product, and to make sure outputs are trustworthy and actionable.</li>
<li>Define and track the metrics that matter &mdash; forecast accuracy, recommendation adoption, labor cost and productivity, and downstream revenue impact.</li>
</ul>
What We&rsquo;re Looking For
Required
<ul><li>3+ years building and shipping ML systems in production (not just notebooks).</li>
<li>Strong Python and the modern ML/data stack (e.g. pandas, scikit-learn, PyTorch or TensorFlow, SQL).</li>
<li>Solid grounding in forecasting, optimization, or recommendation/pricing problems.</li>
<li>Experience taking models from prototype to deployed service, including monitoring and iteration.</li>
<li>Ability to communicate clearly with non-technical stakeholders and translate business problems into technical ones.</li>
</ul>
Nice to have
<ul><li>Experience in hospitality, travel, airlines, retail, or another revenue-management-driven industry.</li>
<li>Familiarity with dynamic pricing, demand modeling, or yield/revenue management.</li>
<li>Experience integrating LLMs into applications (RAG, structured extraction, agentic workflows).</li>
<li>Cloud and MLOps experience (AWS/GCP/Azure, containerization, CI/CD for ML).</li>
<li>Comfort with experimentation and causal measurement (A/B testing, uplift modeling).</li>
</ul>
What We Offer:
<ul><li>Competitive base salary and performance-based incentive plan</li>
<li>Medical, dental, and vision insurance</li>
<li>401(k) plan with company match</li>
<li>Paid time off and holidays</li>
<li>Career advancement opportunities within a rapidly growing company</li>
<li>A chance to be part of the Rebel movement redefining hospitality leadership</li>
</ul>
Why This Role
You'll own meaningful problems end-to-end, see your work move real revenue, and help build a data and AI capability from an early stage. If you want your models to ship and matter rather than sit in a backlog, this is that role. 

Salary Range: $190,000 - $200,000 annually 

At Rebel Hotel Company, we don&rsquo;t manage hotels the old way&mdash;we challenge the status quo. If you&rsquo;re ready to lead with vision, act with ownership, and make your mark in the hospitality world, we want to meet you.</div>

AI Engineer

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