Job Summary  
The Product Solutions Designer on the Enterprise AI and Automation team is, at its core, a design and discovery role. You will dig into ambiguous business problems, map the processes behind them, and design the solution, both the user experience and the workflow underneath it. Design here means more than just visual polish, it means understanding how a process should work before a single screen is built.  

Once you know what needs to exist, you'll build it. You will use AI-assisted development tools and no-code platforms to move from concept to working prototype. Some solutions may stay as low-code internal tools, others will utilize team resources to scale up to full on applications, but you will own the solution end-to-end: discovery, design, and delivery.  

You thrive with autonomy. You are comfortable navigating ambiguity, making decisions with incomplete information, and delivering results without heavy oversight. You want to solve real problems. 

What You’ll Do  

• Intake and discover. Triage requests from across the organization, determine what is worth solving, and conduct the discovery work needed to understand it. This includes process mapping, stakeholder interviews, data analysis, and workflow documentation.  

• Design the solution. Own the end-to-end user experience. Create wireframes, user flows, and interface designs that are clear and functional. Design means both the visual layer and the process underneath it.  

• Build and ship. Use low-code platforms, no-code tools, and AI-assisted development to move from design to working prototype. You do not need to be a software engineer, but you need to be able to deliver something real.  

• Collaborate and scale. Work with the rest of the team to transition prototype solutions into wide-scale applications.  

• Manage your own work. Own your portfolio of projects and communicate status without needing to be closely managed.  

What We Need  

• Experience. 8+ years in roles that combine problem-solving, process improvement, and hands-on solution delivery. The specific title does not matter; the experience does.  

• Design and UX. You design interfaces that are clear, functional, and intuitive. Usability is the priority, you can take a messy business process and turn it into something people actually want to use. Proficiency in Figma or similar tools required.  

• Presence and communication. You can lead intake conversations with stakeholders across the organization, ask the right questions to understand what needs to be built, and translate what you learn into clear designs and recommendations.  

• Discovery and analytical skills. You can dig into a business process, identify where it breaks down, analyze data to understand the real problem, and articulate what needs to change.  

• Building experience. Hands-on experience with low-code platforms (e.g., Retool) and comfort with AI-assisted development tools (e.g., Claude Code, Cursor, Copilot). You do not need to be a traditional software engineer, but you must leverage these tools to ship working solutions.  

• Data fluency. You understand how databases work, can explore data in tools like Snowflake, and are comfortable using AI to generate and refine queries and pull your own insights without relying on a data team.   

Desired Qualifications  

• Technical familiarity. Exposure to data pipelines, integrations, or API-based workflows. Familiarity with JavaScript/Python at a read-and-modify level, enough to work with AI assistance, not enough to architect a platform.  

• Tooling experience. Familiarity with CRM platforms (Salesforce) and project management tools (Jira, GitHub). You will likely encounter both regularly.  

• Process and operations background. Experience with process mapping tools (Lucidchart, Miro, BPMN) and familiarity with business process automation or operations consulting.  

• Comfort with ambiguity and range. You have worked in environments where roles were not rigidly defined and you owned outcomes across multiple functions. You are energized by variety, not overwhelmed by it.  

What You'll Need to Succeed  

• Autonomy and resourcefulness. You do not wait to be told what to do. You can identify problems, propose solutions, and execute. When you do not know how to do something, you figure it out or you reach out for the right resources.  

• Range and adaptability. Some days you are a designer, some days a builder, some days an analyst. You shift between modes comfortably and do not see rigid role boundaries.  

• Bias toward action. You would rather ship something imperfect and iterate than spend weeks perfecting a plan. You know when “good enough” is the right answer, and when something needs real discovery first.  

• Willingness to teach. You are comfortable being the person people come to with AI questions, and you can explain what these tools can and cannot do without overselling or gatekeeping.  

• You lead through craft and influence — mentoring peers, establishing frameworks, and raising the bar for product excellence without a reporting structure. 

• Passion for building products that create meaningful impact in healthcare. 

Base Salary Band: $100,000-$170,000

Compensation: At PatientPoint, we are committed to providing competitive pay and benefits that are in line with industry standards. We analyze and carefully consider several factors when determining compensation, including skills, qualifications, geographic location, and professional experience, which can cause your compensation to vary. The base salary range listed is just one component of PatientPoint’s total compensation package for employees. For additional details on our total benefits package, please review the section “About PatientPoint” at the end of this job description.

At Armis, our Sales Engineers (SE) serve as the linchpin of every prospect engagement. Working closely with our prospects to demonstrate the value of the Armis agentless platform via console demonstrations, proof-of-value deployments, and targeted training sessions.

What you'll do...

Work closely with our prospects to:

• Provide virtual and in-person technical demonstrations
• Deploy proof-of-value installations
• Lead technical training sessions based on POV findings
• Support marketing activities, conferences, speaking engagements
• Consistently and cogently address our prospects needs through astute verbal and written communication skills
• Thrive in a team-oriented culture through delivering a significant individual contribution while collaborating with and strengthening teammates
• Think critically, spanning the sales process through customer support, troubleshooting, and developing new use cases for internal and external consumption.
• Develop prospect facing documentation
• Expected to travel up to 40% of the time on average (can vary by region)

Education:

• BS degrees in computer science, MIS, or equivalent experience required

Experience:

• 5+ years experience in technical positions required (SE, Pre-Sales Engineer, Solutions Architect) ideally for a Cyber Security vendor
• 5+ years of experience in customer-facing or customer support positions
• Solid understanding of networking concepts and technologies
• A demonstrated track record of taking ownership of complex initiatives and producing successful outcomes
• Experience closing complex cyber security SaaS solutions with Enterprise Customers and supporting Sales AE's / RSM's.

Knowledge in one or more of the following:

• IoT, OT, IoMT
• Wireless technologies (WLCs, Meraki, Aruba, etc.)
• Linux Operating Systems
• Virtualized environments
• Network knowledge
• Utility Scripting (Python preferred)

The mission of Speechify is to make sure that reading is never a barrier to learning.

Over 50 million people use Speechify’s text-to-speech products to turn whatever they’re reading – PDFs, books, Google Docs, news articles, websites – into audio, so they can read faster, read more, and remember more. Speechify’s text-to-speech reading products include its iOS app, Android App, Mac App, Chrome Extension, and Web App. Google recently named Speechify the Chrome Extension of the Year and Apple named Speechify its 2025 Design Award winner for Inclusivity.  

Today, nearly 200 people around the globe work on Speechify in a 100% distributed setting – Speechify has no office. These include frontend and backend engineers, AI research scientists, and others from Amazon, Microsoft, and Google, leading PhD programs like Stanford, high growth startups like Stripe, Vercel, Bolt, and many founders of their own companies.

Overview

We're looking to hire for our Data side of our AI team at Speechify. This role is responsible for all aspects of data collection to support our model training operations. We are able to build high-quality datasets at petabyte-scale and low cost through a tight integration of infrastructure, engineering, and research work. We are looking for a skilled Software Engineer to join us.

What You’ll Do

• Be scrappy to find new sources of audio data and bring it into our ingestion pipeline
• Operate and extend the cloud infrastructure for our ingestion pipeline, currently running on GCP and managed with Terraform.
• Collaborate closely with our Scientists to shift the cost/throughput/quality frontier, delivering richer data at bigger scale and lower cost to power our next-generation models.
• Collaborate with others on the AI Team and Speechify Leadership to craft the AI Team’s dataset roadmap to power Speechify’s next-generation consumer and enterprise products.

An Ideal Candidate Should Have

• BS/MS/PhD in Computer Science or a related field.
• 5+ years of industry experience in software development.
• Proficiency with bash/Python scripting in Linux environments
• Proficiency in Docker and Infrastructure-as-Code concepts and professional experience with at least one major Cloud Provider (we use GCP)
• Experience with web crawlers, large-scale data processing workflows is a plus
• Ability to handle multiple tasks and adapt to changing priorities.
• Strong communication skills, both written and verbal.

What we offer

• A fast-growing environment where you can help shape the company and product.
• An entrepreneurial-minded team that supports risk, intuition, and hustle.
• A hands-off management approach so you can focus and do your best work.
• An opportunity to make a big impact in a transformative industry.
• Competitive salaries, a friendly and laid-back atmosphere, and a commitment to building a great asynchronous culture.
• Opportunity to work on a life-changing product that millions of people use.
• Build products that directly impact and support people with learning differences like dyslexia, ADD, low vision, concussions, autism, and more.
• Work in one of the fastest-growing sectors of tech, the intersection of artificial intelligence and audio.

Compensation: The United States base salary range for this full-time position is $140,000-$200,000 + bonus + equity depending on experience

Think you’re a good fit for this job? 

Tell us more about yourself and why you're interested in the role when you apply.
And don’t forget to include links to your portfolio and LinkedIn.

Not looking but know someone who would make a great fit? 

Refer them! 

Speechify is committed to a diverse and inclusive workplace. 

Speechify does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.

Accenture Federal Services is seeking a Cloud Engineer to deliver secure cloud platform implementations supporting government customers. This role focuses on designing, implementing, and managing enterprise-scale cloud infrastructure in classified and sensitive environments. The ideal candidate will thrive in our centralized vision, decentralized command culture that emphasizes ownership within Agile delivery.

What you’ll do:

• Cloud Infrastructure Engineering
  • Design and implement secure, scalable cloud architectures across multiple platforms based on program templates and established best practices
  • Develop and maintain Infrastructure as Code for consistent, repeatable deployments
  • Implement DevOps practices and CI/CD pipelines for rapid, reliable delivery
  • Configure and optimize cloud security controls and compliance measures
  • Design cloud native disaster recovery, backup, and business continuity solutions
  • Troubleshoot complex infrastructure issues and implement performance optimizations
• Agile Delivery & Innovation
  • Operate within Agile framework (participate in sprints, standups, retrospectives, and planning sessions)
  • Collaborate with cross-functional teams in fast-paced development cycles
  • Adapt to changing requirements and priorities while maintaining delivery quality
  • Drive continuous improvement in processes, tools, and methodologies
• Autonomous Operations & Leadership
  • Work independently within centralized vision framework while maintaining team alignment
  • Proactively identify infrastructure needs and optimization opportunities
  • Make technical decisions autonomously while communicating impact to stakeholders
  • Lead by example in demonstrating ownership, accountability, and innovation
  • Mentor team members and share knowledge across the organization
  • Drive technical standards and best practices adoption
• Security & Compliance
  • Implement and maintain security controls in cloud environments
  • Support security audits and compliance assessments for government requirements
  • Manage encryption, key management, and access controls
  • Monitor infrastructure for security threats and implement remediation
  • Develop security documentation and operational procedures
  • Stay current with evolving security requirements and cloud platform updates
• Cross-Platform Integration
  • Integrate multiple cloud platforms and hybrid environments
  • Develop solutions that leverage best capabilities across different cloud providers
  • Implement consistent security and operational practices across platforms
  • Support migration initiatives and platform optimization efforts

What you’ll need:

• 4 years of cloud engineering and infrastructure experience
• 2 years’ experience implementing secure cloud architectures for enterprise or government environments
• Experience with containerization and orchestration technologies

Bonus points if you have:

• Experience with cloud, networking, and security
• Bachelor’s degree in computer science, Information Systems, Engineering, or related technical field
• CompTIA Security+ (current) or equivalent DoD 8570 IAT Level II certification within 6 months of onboarding 
• AWS Solutions Architect Certification
• Familiarity with Infrastructure as Code and DevOps practices
• Experience with enterprise-scale cloud architecture design and implementation
• Experience developing and maintaining Infrastructure as Code: Terraform, CloudFormation, ARM templates, or similar
• Experience with container technologies: Docker, Kubernetes, container orchestration
• Experience with network architecture: VPC design, hybrid connectivity, security groups, load balancing
• Identity and Access Management across cloud platforms
• CI/CD pipeline development and automation
• Proficiency in Python, PowerShell, Bash, or similar scripting languages
• Experience with configuration management tools (e.g. Ansible, Chef, etc.)

Clearance:

Must have an active Secret clearance; TS with SCI eligibility preferred

#clearancejobs

Senior Data Scientist Consultant, Managed Agent Platform (MAP) – Agent Platform Team P2392 

Summary 

The Agent Platform Team, within AI Enablement at 84.51°, owns and manages the core platforms that power data science and AI across the organization. This role sits on the MAP (Managed Agent Platform) squad and is focused on helping stand up a new, centralized platform that simplifies and accelerates the design, development, deployment, and monitoring of AI agents across the organization. 

The MAP is being built in response to growing demand for a flexible, no-code/low-code solution that enables both technical and non-technical users to build and deploy agents without deep engineering overhead. The platform is early-stage — the team is actively evaluating different platforms and tooling, defining workflows, and establishing standards. You will be joining at the ground floor and helping shape what this platform becomes. 

You will be the bridge between the engineers building/maintaining the MAP and the data scientists and agent builders who will use it. You are not building agents for end-clients. Instead, you ensure the platform works for the people on it — that capabilities are tested, documented, and adopted smoothly, and that practitioner needs make it back to the engineering team in a way that shapes the roadmap. 

You’ll bring hands-on familiarity with the open-source agent ecosystem — including frameworks like LangChain, LangGraph, Google ADK, and OpenAI Agents SDK — and apply that knowledge to evaluate platform capabilities, inform design decisions, and help practitioners understand what’s possible. As the platform matures, you’ll help onboard users, develop best practices, and drive adoption across the organization. 

This is a small, engineer-heavy squad that is standing something up from scratch. Everyone pitches in on a bit of everything. Priorities will shift frequently as the platform takes shape. Success in this role is less about fixed technical expertise and more about comfort with ambiguity, good judgment about where to spend your time, and the ability to influence without direct authority. 

Responsibilities 

• Voice of the practitioner: Serve as the primary liaison between data scientists and agent builders and the MAP engineering team. Gather requirements, surface pain points, and translate practitioner needs into actionable feedback that shapes platform decisions, standards, and the roadmap. 

• Platform evaluation & definition: Help evaluate and select platform tooling and contribute to defining core platform capabilities — including agent building workflows, orchestration patterns, tool/API connectivity, observability and tracing, evaluation frameworks, and governance controls. Test and document findings, recommended use cases, limitations, and rollout considerations. 

• Onboarding & enablement: As the platform matures, write guides, maintain documentation, lead training sessions, and run office hours to help data scientists and agent builders adopt the MAP. Serve as a first line of support when teams hit roadblocks. 

• Adoption & communication: Evangelize the MAP to increase awareness and drive adoption across the organization. Produce clear communications and materials for both technical and non-technical audiences. 

• Cross-functional collaboration: Work closely with engineers, the solution architect, and product lead on the squad to ensure platform capabilities have well-defined use cases and that guidelines and best practices are established. Act as an agent-building ambassador to cross-functional teams, explaining recommended workflows and the reasoning behind platform choices. 

• Governance & compliance support: Help validate that platform capabilities meet enterprise requirements around security, compliance, observability, scalability, and data governance. 

Qualifications & Experience 

• Bachelor’s degree in mathematics, statistics, computer science, economics, or a related discipline. 

• 2–4 years of experience in data science, AI/ML development, or applied analytics. 

• 2–4 years of experience in tech consulting, retail analytics, or related professional services. 

• Hands-on experience with Python and SQL. 

• Hands-on experience with one or more agent frameworks (e.g., LangChain, LangGraph, Google ADK, OpenAI Agents SDK, CrewAI, AutoGen) is required. 

• Experience gathering user needs, documenting requirements, and driving issues to resolution with technical teams. 

• Experience partnering with software engineering and/or product management teams. 

• Familiarity with LLMs, prompt engineering, and agentic AI concepts. 

• Exposure to agent platforms is a strong plus. 

Skills 

• Strong written and verbal communication, including the ability to explain technical concepts clearly to non-technical audiences and produce high-quality documentation. 

• Ability to influence across teams and seniority levels without direct authority. 

• Comfort operating in ambiguity — this platform is early-stage, and priorities will shift frequently as the team learns what works. 

• Strong project and time management skills; able to manage multiple priorities with minimal oversight. 

• Deep curiosity about the agentic AI ecosystem and a genuine desire to become a subject matter expert on agent orchestration, evaluation, observability, and deployment patterns. 

• Comfort working on a small, engineer-heavy team where you are often the only non-engineer voice in the room. 

#LI-SSS

Our mission: to enable businesses to grow and reimagine themselves by becoming advocates and champions for their Customers. With deep heritage and expertise in retail – one of the world’s most competitive markets, with a deluge of multi-dimensional data – dunnhumby today enables businesses all over the world, across industries, to be Customer First.

Job Title: Senior Engineer - (Multiple positions available)

Job Location: 3825 Edwards Road, Suite 600, Cincinnati, OH 45209 (May work remotely)

Job Duties:

WHY I DO MY JOB | Job purpose

To contribute to the success of the engineering team by autonomously delivering on the development and deployment of new technology products and/or platforms that drive excellent solutions for clients in order to enable dunnhumby to grow. May work remotely from home office within U.S., consistent with dunnhumby’s remote work policy.

WHAT I DO | Key accountabilities

• Deliver autonomously on development and deployment of complex applications, components, software, platforms or services that are used at scale.
• Conduct requirements analysis, balance different requirements and make technical trade off decisions at application level (e.g. component design).
• Lead exciting end-to-end projects of certain complexity and ensure Service Level Agreements are successfully delivered.
• Define and develop solutions to technical problems that arise.
• Provide advice and guidance to junior colleagues as required to resolve specific challenges they are having and conduct design and code reviews.
• Identify and advise on improvement opportunities and automate and simplify test and operations processes.
• Use your expertise to input into reengineering and design.
• Act as a subject matter expert for focus areas across the technology space.

Job requirements:

• Bachelor’s degree or higher (or foreign educational equivalent) in Computer Science, Mathematics, Physics, Electronics, Engineering or related field.

In addition to the degree, must have at least 5 years of experience in each of the following:

• Software development using Agile;
• Software testing and debugging;
• Cloud infrastructure, management and hosting; and
• Infrastructure as code / DevOps using Kubernetes.

Within this, must have at least 4 years of experience in each of the following:

• Data analysis and modelling;
• Working with big data using Hadoop/HDFS; and
• Utilizing at least 2 of the following programming languages: Scala, C#/C++, Javascript / React, SQL, Python, PHP.

Our mission: to enable businesses to grow and reimagine themselves by becoming advocates and champions for their Customers. With deep heritage and expertise in retail – one of the world’s most competitive markets, with a deluge of multi-dimensional data – dunnhumby today enables businesses all over the world, across industries, to be Customer First.

Job Title: Senior Applied Data Scientist

Job Location: 3825 Edwards Road, #600, Cincinnati, OH 45209 (May work remotely)

Job Duties:

WHY I DO MY JOB | Job purpose

To lead and execute projects to distil complex problems into compelling insights, using the best of dunnhumby science and making recommendations that resonate with clients and lead them to action. May telecommute 100% of the time from their home office, consistent with dunnhumby’s remote work policy.

WHAT I DO | Key accountabilities

• Build strong relationships with internal contacts & external clients to ensure full understanding of client challenges, growth strategy and agreed measures of success for the project.
• Investigate and implement the most appropriate analytical technique for each project, role modelling the re-use & further development of global solutions or code written by others.
• Deploy data science algorithms and market products on chosen tech stack for efficient and cost-effective delivery.
• Identify opportunities to grow client engagement by proactively solving client’s strategic questions, using a mix of products and advanced data science techniques that support executive decision making and calls to action.
• Participate in client meetings as required to present methodology and solutions through effective story telling techniques.
• Work closely with global products team to provide market feedback for enhancing an existing product offering or augmenting the catalogue with a market-based product that can become global offering.
• Ensure smooth running of your data analytics projects and support junior team members with their projects.
• Lead by example by following dunnhumby Quality Assurance processes, ways of working and coding standards.
• Provide advice and support to colleagues to resolve challenges and support code reviews.

Job requirements:

• Bachelor’s degree (or foreign educational equivalent) in Computer Science, Mathematics, Applied Statistics, Engineering or related field.
• In addition to the degree, must have at least 4 years of experience in each of the following:
• Software development, utilizing methodologies and tools such as Agile (Scrum Master) and Code Merge, and programming in languages including PySpark, Python, Flask/Dash, C++, and HTML; and
• Quality Assurance (QA) and Testing, including the development, execution, and maintenance of automated and manual testing frameworks.

Within this, must have at least 2 years of experience in each of the following:

• Handling large data volumes with modern data processing tools, e.g. by using Hadoop, Spark, SQL, and Python;
• Data Interpretation and Insight Analysis; performing data interpretation, insight generation, and analytical analysis to support business and technical decision-making;
• Programming experience on any standard data mining and modelling packages such as Python and R; and
• Applying advanced statistical models and machine learning algorithms to develop and implement solutions to complex analytical and business problems.

Callibrity is a developer owned and managed custom software development consulting company that is dedicated to creating quality software using modern technologies and adding unquestionable business value to companies across multiple industries and verticals. We are problem solvers...people who like a challenge and enjoy working with modern tech stacks. We offer an incredibly collaborative culture and enjoy solving complex problems with our clients. If you are looking for a company where you can grow in your career and that values people, transparency, and flexibility we would like to talk to you.

As a Senior Software Engineer, you are a leader by example, you are a subject matter expert, and you help lead strategic technical direction. You will get to interact with key client stakeholders on a regular basis and use your experience to prove business ROI through innovative greenfield technology solutions. Software Engineer typically have longer tenures and higher retention rates with Callibrity than other companies because the work is challenging and rewarding, we have a strong engineering culture, and we invest in the best people.

Responsibilities:

• Are trusted advisors to our clients and seen as thought leaders in the tech industry
• Are keenly aware of big picture business problems and goals and capable of a leadership role
• Mentor, train, and upskill your Callibrity peers and clients’ teams
• Can solve a wide variety of problems with the appropriate solution drawn from a large subset
• Communicate complex ideas effectively, both verbally and in writing
• Proactively identify problems, challenges, and issues and recommend the best possible solution
• Demonstrate mastery and cable to teach software development best practices (Agile, DevOps, Test Automation, CI/CD, TDD) to others
• Stay ahead of the curve by exploring new technologies including AI, Machine Learning, Cloud, and IoT
• Thrive in an environment where there is close interaction among different roles and teams
• Are admired by the client as someone they can count on, regardless of title or seniority

Requirements:

• 5+ years of experience with web application development and/or SaaS platforms.
• Extensive senior-level development experience with object-oriented languages in Python, FastAPI/Flask, or Java
• Proven experience leading the technical delivery of complex and innovative business functionality.
• Strong understanding of software engineering principles such as design patterns, algorithms, and data structures, and demonstrable application of each in recent projects.
• Cloud experience with AWS, Azure, and/or Google Cloud Platform preferred
• Experience with Docker, Kubernetes, and/or developing applications for a major public cloud provider is a proactive owner who takes accountability for code from development through production.
• Strong knowledge of performance engineering and performance testing.
• Experience with integration technologies (RESTful APIs, messaging systems, etc.)
• Relevant professional experience in Information Technology and/or Consulting
• Four-year degree or successful completion of respected bootcamp/accelerator, or extensive mentorship program
• Successfully solve Callibrity’s CoderPad and Code Pairing Challenges
• Interpersonal skills: Influencer, professionalism and accountability, passion for learning, us not them mentality, shared responsibility
• Embodies Callibrity’s Core Values
• Must be authorized to work in the United States, without sponsorship

Benefits of Being a Callibrity Consultant:

• Health/Vision/Dental insurance effective first day of employment
• 401k match vested immediately
• Profit Sharing Bonus
• Annual professional development stipend ($1,500)
• Paid parental leave
• Paid bench time
• Paid flex time for training, blogging, speaking engagements, and thought leadership
• Paid time off (3–5 weeks depending on level) + 8 holidays
• Competitive industry salary
• Lunch and learns
• Team building events
• Small company feel with the stability of a proven business model
• High employee retention and satisfaction (One of Cincinnati’s Best Places to Work!)

Lead Data Scientist, Relevancy Sciences Data Science & Research – Personalization & Loyalty Strategy (P3764)

Relevancy Sciences Team is responsible for powering relevant, personalized, and scalable customer experiences across Kroger’s e-commerce ecosystem. We build and evolve the science behind search and recommendations that serve millions of customers and support high-scale digital experiences.

We are seeking a Lead Data Scientist to provide technical leadership across search and recommender systems, with a strong focus on modern model architectures, and production-ready machine learning. This role is ideal for someone who combines depth in applied machine learning with strong systems thinking, cross-functional influence, and contributes towards agentic capabilities.

What does the role entail? (Responsibilities)

Technical Leadership, Ownership, and Influence. Own and drive technical initiatives across search & recommender systems. Define and evolve the science strategy for improving content discovery, relevance, personalization, and decision support across digital experiences. Identify high-impact opportunities, make clear technical tradeoffs, and guide the team towards scalable, practical solutions. Rapidly prototype and validate new ideas to accelerate adoption and demonstrate measurable value.

Develop innovative search & recommender systems. Design and build ML solutions tailored to the unique needs of grocery retail domain. Lead the development of systems that improve product discovery and personalization across customer journeys. Bring strong technical and thought leadership on next generation personalization, including the use of Generative AI and agent-based approaches.

Evaluate and improve ML performance. Establish rigorous evaluation methodologies to assess the performance of ML systems across key metrics. Define robust online evaluation frameworks, and guide experimentation strategies that connect model improvements to customer and business outcomes.

Model serving and deployment. Partner closely with Engineering to build and deploy production-ready ML systems. Influence design decisions related to real-time inference, feature access, system integration, monitoring, and reliability. Ensure solutions meet latency, scalability, and operational requirements. Contribute to the evolution of serving and deployment strategies.

Cross-functional leadership. Work closely with Product, Engineering, and business stakeholders to translate needs into clear problem statements, hypotheses, and execution plans. Drive alignment across teams and influence decisions through clear communication of tradeoffs, risks, and expected outcomes.

Mentoring and knowledge sharing. Mentor data scientists and lead technical reviews to improve model quality, experimentation rigor, and systems thinking. Promote best practices in reproducibility and evaluation. Contribute to building a strong, learning-oriented team culture.

What skills and experience do you need? (Requirements)

• Bachelor’s, Master’s, or PhD in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related quantitative field.
• 6+ years of experience applying machine learning to real-world problems with strong experience in search and recommender systems. Strong understanding of approaches such as embeddings and multi-stage decision systems.
• Strong proficiency in Python and SQL, with experience working on large-scale data using tools such as Spark.
• Experience with modern machine learning and deep learning frameworks such as PyTorch or TensorFlow.
• Strong foundation in statistics, experimentation, and data analysis, including design of experiments and A/B testing.
• Familiarity with large language models, foundation models, and emerging AI capabilities, including where they are applicable and where they are not.
• Experience evaluating or prototyping GenAI-based solutions is preferred.
• Experience partnering with engineering teams to deploy and maintain machine learning systems in production.
• Understanding of real-time systems, model serving, feature pipelines, and monitoring.
• Ability to make practical tradeoffs between model complexity, performance, latency, and scalability.
• Demonstrated ability to lead technical work across projects and influence direction across data science, engineering, and product teams.
• Experience mentoring or guiding other data scientists and contributing to a strong technical culture.
• Experience working with cloud platforms such as GCP or Azure.
• Experience in retail, e-commerce, or high-scale consumer domains is a plus.

Why join our team? (Rewards)

Impact millions of people. As a member of our data science team, you will have the opportunity to make a tangible difference in the lives of millions of customers by delivering relevant and personalized recommendations that enhance their grocery shopping experience. Your work will directly contribute to increasing customer satisfaction and loyalty, driving business outcomes for our company.

Continuous learning and development. Challenge yourself. We are committed to fostering a culture of continuous learning and development. You will have access to resources and support for expanding your knowledge and skills in cutting-edge technologies, including recommender systems, machine learning and artificial intelligence. Our team encourages exploration and experimentation, providing opportunities to stay at the forefront of industry advancements.

Work on new developments in recommender systems. Join a team at the forefront of innovation in recommender systems and AI. You will have the chance to contribute to pushing the boundaries of what’s possible in personalized recommendation technology. You will have the chance to work on exciting projects that leverage the latest developments in deep learning architectures and data science methodologies.

#LI-SSS

This opportunity is tailored for students seeking a co-op or internship experience. 

• Gather and define user requirements for tools and solutions
• Analyze processes and identify gaps
• Assess systems and their capabilities versus user and process requirements
• Facilitate and gather feedback from client team members
• Analyze capacity of machines or production through time studies
• Perform root cause analysis and use data to draw conclusions
• Interpret financial statements to identify opportunity areas
• Perform financial modeling and forecast financial metrics for clients
• Analyze supply chain and pricing strategies
• Develop data visualizations for clients to enable data-driven decision making
• Load and clean data, manipulating structure and connecting data tables where needed
• Build skillset in some of the following: Power BI, Excel, R, Python, SQL
• Apply all statistical results to a business setting with clear resulting actions
• Develop PowerPoint presentations for client report outs
• Travel as needed to meet client needs, up to 4 days/week

• Consulting and Change Management skills
• Ability to build relationships and collaborate with clients and AMEND team members
• Project and Time Management
• Robust problem-solving skills
• Capacity to focus on goals and manage action items, prioritization, and accountability
• Strong self-awareness to seek constant feedback
• Motivation and excitement to drive your continued development

Applicants for employment in the US must have work authorization that does not now or in the future require sponsorship of a visa for employment authorization in the United States and with the Kroger Family of Companies (i.e. H1-B visa, F-1 visa (OPT), TN visa or any other non-immigrant status)

You will be joining a team of data scientists operating within the PL&S at 84.51°. Our team partners across multiple portfolios, including Our Brands, Kroger Personal Finance, and the Kroger Enterprise Marketing organization, to support media strategy & execution, targeting, measurement, and enterprise level marketing initiatives.

We work closely with the Our Brands and Kroger Personal Finance teams to plan, execute and measure targeted media and deliver insights that drive growth and efficiency. The team leads the execution of brand loyalty mailers for the Big 3 Our Brands, with a focus on rewarding high‑brand‑loyal households that drive the greatest business value. We also collaborate with Kroger Marketing to execute and measure activations across a range of initiatives, ensuring data driven insights inform business decisions.

Our team is known for being subject matter experts of KPM processes for Kroger Model and owners of a broad set of analytical and external-facing tools. We solve complex client and customer problems by applying the most appropriate statistical and analytic approaches to answer meaningful business questions. In this role, you will be on the front lines supporting Sales and Account Management partners, while also developing deep expertise in retailer data.

You will work hands-on with large-scale retailer databases and leverage the full suite of 84.51° technical and visualization tools, including Python, SQL, Excel, Power BI, and internal platforms, to deliver timely, relevant, and actionable insights. We expect all data scientists on our team to be deeply engaged in advanced analytics and comfortable working directly with data to drive impact.

Responsibilities:  

• Lead end-to-end analytics and data science projects, managing stakeholders and delivering solutions on time, within scope, and to business objectives.
• Develop a strong understanding of the end-to-end CRM (Our Brands Loyalty Mailer) targeting and measurement process to ensure the timely, accurate delivery of mailers and the generation of actionable insights. 
• Apply optimizations and scientific enhancements in targeting to improve customer engagement and maximize ROI.
• Partner closely with Sales and Account Management to own the analytic relationship for OB, driving engagement and shaping analytical offerings through feedback and insight.
• Translate complex first-party data into clear, actionable customer stories and recommendations that inform media strategy, optimization, and business decisions.
• Drive continuous improvement through stronger measurement methodology, increased automation, and clearer data visualization that leads to more actionable insights.
• Attain deep expertise in 84.51° and KPM data assets, measurement techniques, QA processes, and analytic capabilities, confidently applying them to internal and external business needs.
• Collaborate across data science, product, engineering, and capabilities teams to validate new use cases, assess data quality, and support innovation.
• Mentor and support junior data scientists through onboarding, coaching, and knowledge sharing, while championing best practices across the data science community.

Qualifications, Skills and Experience: 

• Bachelor’s degree in statistics, mathematics, business analytics, economics, marketing, or related discipline.
• 2+ years of experience in retail, ad technology, digital media, and/or advertising analytics.
• 2+ years of experience in data science, ad technology, digital media, and/or advertising analytics.
• 2+ years of experience in extracting insights from large databases, translating market research into actionable solutions and presenting findings and recommendations to clients.
• 2+ years of experience using advanced algorithms, programming languages (Python, SQL), or technologies in the development of technical analytics solutions, capabilities, and ad hoc analyses.
• Experience working cross-functionally to continuously improve existing solutions based on client feedback and validated demand.
• Strong interpersonal and communication skills including excellent verbal, written, presentation, and consultation skills.
• Comfortable conveying complex data science techniques and methodological approaches to less technical audiences – both internal and external.
• Strong analytical, problem-solving and decision-making skills.
• Strong data visualization and business acumen skills to link analysis to business impact (grocery and/or retail experience is a plus).
• Natural curiosity that welcomes and embraces ambiguity and change, with a willingness to try new things and to fail.
• Excellent attention to detail, organization skills and ability to work in a collaborative environment.

#LI-AB1

The Consumer Research team at 84.51° uncovers the “why” that complements the deep behavioral understanding 84.51° uniquely delivers.  Our focus is uncovering the “Why,” integrating it with the “What,” and turning these insights into human stories and business recommendations that compel actions to be taken that delight our customers in ways no other retailer can.  We strive to consistently bring this human understanding to the business and serve as a strategic partner to leaders at 84.51° and Kroger. 

A Senior Researcher on our Research Insights team is accountable for the creation and execution of research projects start to finish, applying best practices and standards to projects, and delivering actionable results to stakeholders- both internal and external. The role will execute research across a range of methodologies (Quantitative and Qualitative).  Additionally, this role is responsible for leveraging existing data for ad hoc analysis to support a holistic view that raises the collective understanding of our customers’ motivations and perceptions.

CORE RESPONSIBILITIES

Research Execution & Delivery:

• Independently execute research projects end‑to‑end once scope and approach are aligned, including:
• Translating business questions into research objectives
• Designing or customizing questionnaires / discussion guides
• Managing vendors and internal partners through fieldwork
• Conducting analysis and synthesis across qualitative, quantitative, and secondary data
• Developing clear, decision‑oriented insights and recommendations
• Apply strong judgment in balancing speed, depth, feasibility, and cost in execution
• Ensure quality, rigor, and clarity across all deliverables

Stakeholder & Project Management:

• Serve as the day‑to‑day research owner for assigned projects
• Proactively manage timelines, dependencies, and risks
• Communicate clearly with partners on status, tradeoffs, and implications
• Show up as a confident research partner in working sessions and readouts

Ways of Working & Team Contribution:

• Operate effectively within CR request intake, scoping, and prioritization processes
• Leverage existing research, products, and tools before defaulting to custom solutions
• Contribute to shared learning by documenting work, sharing best practices, and flagging patterns across projects
• Partner closely with Lead Researchers, Consultants, CX Measurement, and Research Operations

QUALIFICATIONS, SKILLS, AND EXPERIENCE:

• Experience executing multiple research projects simultaneously with minimal oversight
• Comfort working across data types (qual, quant, secondary) and synthesizing into clear stories
• Strong analytical thinking and ability to translate findings into implications and recommendations
• Clear, concise communicator—able to present insights to non‑research audiences
• Strong organizational skills and attention to detail
• Comfortable operating in a fast‑moving, sometimes ambiguous environment
• Tools & Platforms (experience with some preferred): Qualtrics, SPSS/R/Python/Alteryx, Tableau/PowerPoint, insights repositories, and qualitative platforms (e.g., VoxPopMe)

EDUCATION:

• Bachelor’s degree or equivalent, ideally in business, marketing, social sciences, psychology or analytics/statistics.
• 3-5 years of industry experience

#LI-AB1

Lead Cloud Engineer (P486)

Cincinnati / Chicago

SUMMARY

The Lead Cloud Engineer will help technology teams architect and operate cloud infrastructure on Microsoft Azure, applying Cloud Engineering principles and defining solutions where gaps exist. They will collaborate with teams to deliver cloud engagements that achieve business objectives, with a strong emphasis on Azure management, governance, and day-to-day operational excellence (identity, networking, security, cost, and reliability). The role owns primary responsibility for driving/evolving the Cloud Engineering team capabilities in Azure and Infrastructure as Code, including Terraform standards and reusable modules. The role is responsible for day-to-day operational response and problem resolution for referred incidents and is a participant in an on-call rotation.

RESPONSBILITIES:

• Prioritize referred incidents from the Service Desk, Engineering/Data Science projects and other technology teams and provide/guide problem resolution for those incidents, including managing any necessary vendor engagement and serving as escalation point for the team
• Own and improve Azure platform operations and administration, including subscription/resource organization, RBAC/identity integration, networking, security controls, monitoring, and cost management
• Responsible for managing and improving our Terraform ecosystem (Terraform Cloud/Spacelift, policy/standards, and reusable modules with best practices built in)
• Implement and enforce Infrastructure as Code workflows (code review, testing, CI/CD, drift detection, and remediation) to improve repeatability and auditability
• Responsible for input to and for meeting team SLO targets and collaboratively ensuring team objectives are met
• Independently define, prioritize and execute project tasks and plans to deliver cloud-related infrastructure and solutions
• Document work and solutions appropriately and review Cloud Engineering team documentation for accuracy/completeness
• Contribute technical/procedural ideas to Cloud Engineering team operations and define/execute strategies to integrate these solutions as appropriate
• Engage with other technology and infrastructure teams as necessary to complete tasks
• Responsible for one or more cloud-related technologies including complete ownership of all aspects of the technology (maintain, upgrade, train, mentor, document)
• Participate routinely in team on-call rotation

QUALIFICATIONS, SKILLS, & EXPERIENCE

• 4-year degree in a technology related discipline or equivalent work experience
• 5+ years of hands-on experience designing, administering, and operating production workloads in Microsoft Azure
• 5+ years of experience with Infrastructure as Code (IaC) and cloud automation
  • Required IaC deep tooling experience: Terraform/OpenTofu, module creation and management, and policy/guardrail application.
• 5+ years of experience with SDLC and working with Agile development teams
• Microsoft Azure Administrator Associate (or higher) certification preferred
• Experience with container technologies (e.g., Docker) and familiarity with Kubernetes/AKS are a plus
• Nice to have tooling experience:
  • Python or other high-level interpreted programming language
  • GitHub Actions
  • Helm
  • Datadog or other enterprise observability tool
  • Artifactory or other enterprise package management system
• Ability to manage small to medium size IT-related projects, solving related problems and working to tight deadlines while under pressure
• Strong interpersonal and communication skills with demonstrated experience leveraging these skills with technical teams and non-technical business units
• Desire to learn new technology and grow across different areas of technology
• Demonstrated ability to prioritize own workload with multiple responsibilities and adaptability to changes in those priorities

#LI-SSS

Senior Data Scientist Consultant, SPI – Agent Platform Team

Summary

The Agent Platform Team, within AI Enablement at 84.51°, owns and manages the core platforms that power data science and AI across the organization. This role sits on the SPI (Science Platform Innovation) squad and is focused specifically on the Databricks environment and its evolving AI/ML capabilities.

You will be the bridge between the engineers building and maintaining our Databricks platform and the data scientists who use it every day. You are not building models for end-clients. Instead, you ensure the platform behaves as expected for the people on it—that new capabilities are tested, documented, and adopted smoothly, and that practitioner pain points make it back to the platform team in a way that shapes the roadmap.

You’ll build deep familiarity with Databricks’ infrastructure and AI powered capabilities —including Genie Code, Genie spaces, Agent Bricks, MLflow, and other features as they emerge—as well as the Unity Catalog governance layer that underpins them. You’ll test and evaluate new Databricks features and relevant third-party integrations from the perspective of an end-user, document your findings, and help the team decide what to adopt, how to roll it out, and what to skip.

This is a small, highly collaborative squad. Everyone pitches in on a bit of everything. Priorities shift frequently as the Databricks roadmap evolves. Success in this role is less about fixed technical expertise and more about comfort with ambiguity, good judgment about where to spend your time, and the ability to influence without direct authority.

Responsibilities

• Voice of the practitioner: Serve as the primary liaison between data scientists using Databricks and the platform engineering team. Gather requirements, surface pain points, and translate practitioner needs into actionable feedback that shapes platform decisions and roadmaps.
• Technology evaluation: Lead the testing and evaluation of new Databricks capabilities (e.g., Mosaic AI features, Model Serving enhancements, Genie, new Unity Catalog functionality) and relevant third-party tools. Document findings, recommended use cases, limitations, and rollout considerations. Over time, this may evolve from hands-on beta testing toward designing and coordinating evaluation efforts across groups of practitioners.
• Onboarding & enablement: Write guides, maintain documentation, lead training sessions, and run office hours to help data scientists adopt new platform capabilities. Partner with Learning & Development where appropriate. Serve as a first line of support when teams hit roadblocks.
• Adoption & communication: Evangelize Databricks capabilities to increase awareness and drive adoption. Produce clear release notes, communications, and materials for both technical and non-technical audiences.
• Cross-functional collaboration: Work closely with the solution architect, cloud engineer, and product senior on the squad to ensure proposed technologies have well-defined use cases and that guidelines and best practices are established. Act as a data science ambassador to cross-functional teams, explaining recommended workflows and the reasoning behind platform choices.
• Governance & compliance support: Help validate that new platform capabilities meet enterprise requirements around security, compliance, observability, and data governance (e.g., Unity Catalog lineage, Azure connectivity).

Qualifications & Experience

• Bachelor’s degree in mathematics, statistics, computer science, economics, or a related discipline.
• 2–4 years of experience in data science, AI/ML development, or applied analytics.
• 2–4 years of experience in tech consulting, retail analytics, or related professional services.
• Hands-on experience with Python, SQL, PySpark and Databricks
• Experience gathering user needs, documenting requirements, and driving issues to resolution with technical teams.
• Experience partnering with software engineering and/or product management teams.
• Familiarity with LLMs, prompt engineering, or agentic AI concepts is a strong plus.
• Experience with the Databricks ecosystem (Unity Catalog, MLflow) is a strong plus.
• Exposure to agent frameworks (e.g., LangChain, LangGraph, CrewAI, AutoGen) is a plus.

Skills

• Strong written and verbal communication, including the ability to explain technical concepts clearly to non-technical audiences and produce high-quality documentation.
• Ability to influence across teams and seniority levels without direct authority.
• Comfort operating in ambiguity—priorities shift frequently, and you need good instincts about where to focus.
• Strong project and time management skills; able to manage multiple priorities with minimal oversight.
• Curiosity and enthusiasm for emerging AI technologies and a genuine desire to become a subject matter expert on the Databricks platform and its AI capabilities.

#LI-SSS

Lead API Platform Engineer (Cincinnati / Chicago) P181

About 84.51°

84.51° is a data science and technology company (owned by Kroger) that turns customer data into decisions that improve how people shop. Engineers here work with modern cloud and data tech at meaningful scale, alongside product, data science, and business teams.

The role

We’re hiring a Lead API Platform Engineer to join our Application Delivery team within Platform Engineering. This is an individual contributor (IC) technical lead role, owning the API gateway experience end-to-end — from pre-production through production. You’ll help shape technical direction, mentor engineers, and continuously improve our on-call/escalation rotation — participating and fielding gateway-related production issues when on rotation.

If you meet most—but not all—requirements, we still encourage you to apply.

What you’ll do

• Own our gateway platforms: Maintain and evolve our Kong Enterprise API Gateway and Azure Application Gateway configurations, standards, and best practices—and help design what’s next.
• Strengthen API security: Implement and promote API security standards, including OAuth2, JWT, and SAML, along with access controls and encryption.
• Improve reliability and performance: Monitor, troubleshoot, and optimize using Datadog. Tune latency, caching behavior, and rate limiting to support high-performing APIs.
• Automate delivery: Build and maintain automation and CI/CD workflows (using GitHub Actions) for gateway deployments and policy/configuration updates.
• Enable great developer experience: Improve how teams build and test APIs by standardizing gateway onboarding, providing self-service patterns, and supporting reliable local development workflows (e.g., local gateway tooling, mock/test routes, and clear “run it locally” docs).
• Shape work for success: define and decompose scope into ready-to-build requirements (clear user stories and acceptance criteria), aligning on delivery standards, and proactively removing blockers to keep execution on track.
• Support production operations: Provide L2/L3 support, participate in an on-call rotation, lead root-cause analysis, and drive permanent fixes.
• Collaborate and document: Partner with development, QA, security, and architecture teams. Create clear documentation, SOPs, and onboarding materials to help teams ship confidently.

What we’re looking for

• Bachelor’s degree (Master’s degree desired) typically in Computer Science, Management Information Systems, Mathematics, Business Analytics or another technically strong program.
• 5+ years of hands-on experience operating API gateways in production environments (especially Kong)
• Strong API fundamentals (REST, JSON) and security best practices
• Experience working in a public cloud environment, plus solid networking knowledge (DNS, firewalls, load balancers) – Azure preferred but not required
• Comfort scripting and/or coding in one or more languages (e.g., Python, Shell, Java, Node.js)
• Familiarity with DevOps/Agile practices, Docker/Kubernetes/Helm, and Terraform (or other IaC tools)
• Clear communication skills and a collaborative mindset in a fast-moving environment

#LI-SSS

Senior Data Scientist / P3358

Summary

We are seeking a Senior Data Scientist to join our Proprietary Models team. In this role, you will play a critical part in developing, evaluating, and democratizing our foundation models portfolio—including embeddings, pre-trained LLMs, and fine-tuned language models. You will build and optimize embedding pipelines, design rigorous evaluation frameworks, drive models from experimentation to production, and guide business stakeholders through the process of integrating these models into their workflows. The ideal candidate combines deep technical expertise in machine learning and AI with strong problem-solving abilities, a commitment to engineering excellence, and a passion for enabling others to leverage AI effectively.

Responsibilities

Your work will cover a lot of ground, from engineering data pipelines to testing novel AI methodologies to guiding business stakeholders. You will be expected to flex between these skill domains as work progresses through its lifecycle, and to collaborate within a team to make it all happen.

• Develop and optimize embedding pipelines for vector search, retrieval-augmented generation (RAG), and downstream ML applications.
• Conduct rigorous model testing, evaluation, and validation against quality metrics, performance benchmarks, and reliability standards prior to release.
• Design and execute proof of concepts to demonstrate feasibility for specific business problems.
• Build and maintain automated testing frameworks for model performance, data quality, and pipeline integrity.
• Collaborate with MLE/Researchers/Engineers to develop, fine-tune, and deploy foundation models.
• Perform exploratory data analysis (EDA), feature engineering, and data preprocessing to support model development.
• Develop and maintain Jupyter notebooks, scripts, and workflows for reproducible experimentation and analysis.
• Contribute to building and maintenance of code packages, APIs, hosted applications, and other foundation model delivery mechanisms.
• Troubleshoot integration challenges and provide technical guidance for model integrations.
• Guide business stakeholders, data science and engineering teams through adoption and integration of foundation embedding and generative AI models.
• Create documentation, user guides, and best practices for internal model adoption and usage.
• Serve as a liaison between the Foundation Models team and business stakeholders, gathering feedback to inform the development roadmap.

Qualifications and Experience

Required

• Bachelor’s degree in Data Science, ML, Computer Science, or a related discipline
• 3+ years of hands-on experience in data science or machine learning roles
• 3+ years’ experience building in Python using big data tools (e.g. Hadoop, Databricks)
• Hands-on experience building processes incorporating LLMs, embeddings, or related model architecture
• Experience applying embeddings within AI projects and machine learning applications
• Track record of shipping, measuring, and maintaining machine learning models in production
• Exceptional communication skills with ability to explain complex technical concepts to non-technical audiences
• Experience in stakeholder management, technical documentation creation, and cross-functional collaboration

Preferred

• Experience building in cloud data platforms (i.e. Azure, GCP)
• Previous developer relations, technical evangelism, or advocacy experience
• Background in NLP, conversational AI, or generative AI applications
• Open-source contributions or thought leadership in AI/ML community

#LI-SSS

DIRECTOR, DATA SCIENCE - SUPPLY CHAIN, OPERATIONS, REPLENISHMENT

Cincinnati, OH

Chicago, IL

SUMMARY:

The Supply Chain, Operations, and Replenishment  (SCORe) team is responsible for creating for cutting edge supply chain and operations sciences to meet Kroger’s need now and in the future, ensuring that we deliver value for our Kroger stakeholders and the enterprise.  This role will lead the supply chain data scientists and partner heavily with our Product and Engineering community to develop the best solutions for our stakeholders within our supply chain workstreams.

RESPONSIBILITIES:

• Influence and partner with SCORe team leaders to set the vision and future road map by developing immediate and long-term strategic plans in supply chain and operations
• Partner with the other SCORe Tech DSR Leads to develop and oversee innovation/capability roadmaps to support strategic supply chainplans
• Bring transformational, innovative thinking to the SCORe team, creating and/or improving ways of working, products, sciences, tools and initiatives
• Develop and manage stakeholder relationships within 84.51° and Kroger to drive better decisions across the Supply Chain space
• Understand business priorities and project value to make prioritization decisions
• Partner with cross-functional leaders to ensure shared goals that enable delivery of science services and insights at scale
• Enable & manage a team of data scientists in delivering strategic objectives and work plans while developing their individual technical and business skills

QUALIFICATIONS, SKILLS, AND EXPERIENCE:

• 7+ years developing analytical solutions using advanced AI, Machine learning, and optimization methods
• 7+ years querying data from relational databases using SQL/Python to develop analytical solutions
• 7+ years with data wrangling, data cleaning and prep, problem framing, and analysis
• Experience with managing, recruiting, training, developing, coaching, and/or inspiring highly technical associates
• Proficient in technology stack (Azure, Databricks, Python, Spark)

• Experience applying data science capabilities to supply chain and operations business problems

• Experience with developing, coaching, and/or inspiring highly technical associates
• Ability to work in a highly collaborative cross functional environment
• Comfort with fast pace and multiple moving parts, anticipating and solving for future barriers/ changes 
• Excellent interpersonal, collaboration, and communication skills
• Strong business acumen
• Strong academic background in mathematics, statistics, computer science, economics, or similar discipline
• Strong analytical, creative problem-solving and decision-making skills
• Ability to create computationally efficient solutions
• Natural curiosity and passion around data, analysis and insights
• Welcomes and embraces change
• Ability to work fast yet accurately
• An openness and willingness to try new things and to fail 

An ideal candidate has a strong track record of: 

• Building stakeholder relationships at a senior level
• Internal or External client exposure and strong understanding of client’s business needs
• Ability to present technical solutions to non-technical audience
• Managing, recruiting, training, developing, coaching, inspiring and/or leading others
• Championing an inclusive culture and embracing 84.51° D&I initiatives 
• Creating and/or improving large-scale processes or initiatives
• Leading Data Scientists through product life cycle and projects
• Independently creating solutions and solving open-ended and/or complex problems, analyzing both successes and failures
• Collaborating across all functions of 84.51° 
• Providing direct, constructive feedback to peers and junior data scientists 
• Making data-driven decisions and priority calls
• Clearly articulating their point-of-view
• Comfortability with fast pace and multiple moving parts, anticipating and solving for future barriers/ changes 

#LI-SSS

SENIOR DATA SCIENTIST (P2408)

SUMMARY:

The Core Science team is responsible for some of our most foundational data science products including enterprise-wide segmentations and store measurement tools. As Senior Data Scientist on the Core Science team, you will build and maintain our new Customer Dimensions and Functional Loyalty. Our team plays a crucial role in building core segmentations that are used across the business in various functions like customer reporting and targeting.

In this role, you will maintain and enhance existing dimensions, support business use of dimensions, build and monitor data quality dashboards, and develop new customer dimensions to expand our view of customers. This includes responding to time-sensitive requests for deep-dive analyses, managing routine processes, and innovation of new segmentations.

You will leverage a diverse technical toolkit including Power BI for dashboard development, GitHub for code management and version control, and PySpark for programming. Additionally, you'll have opportunities to explore the use of embeddings and incorporate AI technologies to enhance our analytical capabilities and create more efficient solutions.

Success in this role requires strong analytical skills and business insights combined with intellectual curiosity and adaptability. We're looking for someone who embraces change, demonstrates enthusiasm for learning new methodologies, and can balance maintaining existing systems while innovating for the future.

RESPONSIBILITIES:

• Effectively managing projects, tasks and stakeholders to ensure that projects are delivered on time, within budget and to brief specification while ensuring minimal downtime and maximum utilization.
• Interpreting results and developing actionable recommendations from the data analysis to build relevant customer stories for clients.
• Identifying and implementing artificial intelligence solutions to enhance business processes, drive operational efficiencies, and deliver increased value to stakeholders.
• Quality Assurance of own code and that of team members to ensure the highest quality work is being delivered to our clients.
• Identifying opportunities for standardization & automation of existing solutions and processes to enable 84.51° to realize the maximum potential from our teams.
• Challenging and improving 84.51° analytical capabilities/products.
• Working closely with key internal stakeholders to ensure sound knowledge of client objectives and customer insight, to subsequently design best-in-class solutions.

QUALIFICATIONS, SKILLS, AND EXPERIENCE:

• 2+ years of experience in consulting or professional services
• 2+ years of experience in extracting insights from large databases, translating market research into actionable solutions and presenting findings and recommendations to clients
• 2+ years of experience using advanced algorithms, programming languages, or technologies in the development of technical analytics solutions or capabilities.
• Experience querying data from relational databases using SQL.
• Experience using R, Python, or other similar statistical software to develop analytical solutions.
• Experience with data wrangling, data cleaning and prep, dimensionality reduction.
• Experience with Big Data concepts, tools, and architecture (e.g. Hadoop, Pig, Hive, Spark, Sparkling Water).
• Ability to create computationally efficient solutions.
• Strong academic background in mathematics, statistics, computer science, economics, or similar discipline.
• Data visualization skills and ability to present technical solutions to non-technical audience.
• Strong interpersonal and communication skills.
• Strong analytical, creative problem-solving and decision making skills
• Strong business acumen; grocery and/or retail experience is a plus.
• Passionate about data, analysis and insights.
• Natural curiosity that welcomes and embraces change and willingness to try new things and to fail, particularly in exploring emerging technologies and AI applications.
• Ability to work in a highly collaborative environment.

#LI-SSS

Director, Software Engineering – Agentic Foundations (P4474)

PREFERRED LOCATION: Cincinnati / Chicago

SUMMARY:

The AI Enablement team at 84.51° is seeking a Director of Software Engineering for its Agentic Foundations team. This team is responsible for designing, developing, and maintaining the agentic backbone of the Kroger enterprise, including platforms, patterns, and tools to support the best practice development of AI agents.

The Director of Engineering requires a unique mix of software engineering and AI skills necessary to lead the technical design of platforms, patterns, and tools to support the enterprise agentic ecosystem. This role has a focus on providing the technical leadership needed for engineering and data science development teams implementing solutions like agent/MCP/scorer/prompt registries, agent-related tools to aid in the development and monitoring of best practice agents and tools, and managing low-code and no-code agent platforms that integrate with agentic support.

RESPONSIBILITIES:

• Partner with the Director of Product Management for Agentic Foundations to jointly lead the space for the Kroger enterprise
• Lead and manage a team of engineers, guiding them in the design and development of their product/platform areas and in the management of their own reports
• Lead and manage hiring efforts for engineers on the Agentic Foundations team, including finding interview panelists, writing interview guides and questions, and assisting with coding screening questions
• Own and manage offshore reliability engineering teams
• Provide in-depth technical leadership in the scoping and implementation of enterprise-grade solutions to support agents across the Kroger enterprise
• Provide operational leadership across agentic platforms, ensuring enterprise-grade reliability, observability, and incident management
• Maintain an up-to-date expertise on agentic workflows, frameworks, platforms, and best practices to identify and inform new capabilities for implementation
• Foster a collaborative and innovative team environment, encouraging professional growth and development among team members
• Reduce the development time of the team by leveraging agentic SDLC tooling provided by the enterprise
• Lead the abstraction of tooling and services to user-friendly interfaces like APIs, Python packages, or UIs
• Understand business requirements and trade-off scale, risk, and accuracy to maximize value and translate research into consumable products or services
• Guide the development teams to follow software development standards, including version control, documentation, testing, and support
• Make time-sensitive decisions and solve urgent problems without escalation

QUALIFICATIONS, SKILLS, AND EXPERIENCE:

• 7+ years professional experience with cloud-based software architecture focused on scalability, performance, and reliability
• 7+ years professional experience with end-to-end SDLC leveraging CI/CD and AIOps/MLOps, including experience with agentic SDLC tooling
• 7+ years professional experience with large-scale AI/ML systems, including 2+ years with GenAI and deep learning methods
• Professional experience with production-grade agentic systems, including concepts like design and development, evals, deployment, and monitoring
• Professional experience with AI/ML frameworks and tooling (PyTorch, OpenAI SDK, LangChain, autogen)
• Professional experience with AIOps/MLOps tooling and concepts (MLflow, Model Registry, Model Monitoring)
• Professional experience with scaling and deploying AI/ML systems using tooling in Microsoft Azure and Google Cloud, including CI/CD, containerization, orchestration, and API development (in particular FastAPI)
• Professional experience with Kubernetes (AKS) and Helm
• Professional experience with Python
• Professional experience with infrastructure-as-code using Terraform
• Professional experience leading technical teams and consulting with customers, including managing senior engineers, communicating complex technical topics, and driving outcomes in ambiguous environments
• Skilled in partnering with product management peers to jointly define product and team direction and priorities
• Education: Bachelor’s degree or higher in Software Engineering, Computer Science, Machine Learning, or a related field

#LI-SSS

#LI-Remote

Lead Software Engineer – Agentic Foundations (P4475, P4477)

LOCATION: Cincinnati / Chicago

SUMMARY:

The AI Enablement team at 84.51° is seeking a Lead Software Engineer for its Agentic Foundations team. This team is responsible for designing, developing, and maintaining the agentic backbone of the Kroger enterprise, including platforms, patterns, and tools to support the best practice development of AI agents.

The Lead Software Engineer will provide hands-on technical leadership across architecture, implementation, and operations of core agentic capabilities, including agent/MCP/scorer/prompt registries, evaluation and monitoring tooling, and low-code/no-code agent platforms that abstract complexity for developers and business users. You will partner closely with product management, data science, and engineering peers and leaders to deliver enterprise-grade capabilities that accelerate time-to-value, improve quality and reliability, and promote compliant, best-practice use of agentic systems.

RESPONSIBILITIES:

• Lead the design, development, and operation of core agentic platforms, services, and tooling used across the Kroger enterprise
• Own technical outcomes for a more specific product area, such as registries (agent/MCP/scorer/prompt), evaluation frameworks, observability/monitoring, SDKs/APIs/UIs, and low-code/no-code agent platforms
• Provide in-depth technical leadership to scope and implement scalable, secure, and reliable solutions;
• Uphold standards for architecture, code quality, testing, and documentation
• Partner with the Agentic Foundations leadership, as well as engineering and data science leads, to plan quarters/cycles/sprints and ensure efficient, predictable delivery
• Work with offshore reliability engineering teams to ensure SLAs are upheld
• Occasional participation in level 2 on-call support for production systems
• Abstract complex capabilities into developer-friendly interfaces (APIs, Python packages, CLIs, and UIs) to reduce friction and accelerate adoption
• Drive operational excellence across platforms, including incident management, on-call support, capacity planning, and cost optimization
• Mentor and guide engineers through code reviews, architecture discussions, and pairing; contribute to team growth, onboarding, and enablement

QUALIFICATIONS, SKILLS, AND EXPERIENCE:

• Professional experience with cloud-based software architecture focused on scalability, performance, and reliability
• Professional experience with end-to-end SDLC leveraging CI/CD and AIOps/MLOps, including experience with agentic SDLC tooling
• Professional experience with large-scale AI/ML systems, including 1+ years with GenAI and deep learning methods
• Professional experience with AI/ML frameworks and tooling (PyTorch, OpenAI SDK, LangChain, autogen)
• Professional experience with AIOps/MLOps tooling and concepts (MLflow, Model Registry, Model Monitoring)
• Professional experience with scaling and deploying AI/ML systems using tooling in Microsoft Azure and Google Cloud, including CI/CD, containerization, orchestration, and API development (in particular FastAPI)
• Professional experience with Kubernetes (AKS) and Helm
• Professional experience with Python
• Professional experience in ambiguous environments
• Skilled in problem solving, analytic thinking, and creativity
• Skilled in planning, organization, and verbal/written business communication
• Skilled in maintaining a positive leader persona in ambiguous and changing environments
• Demonstrated excellence as a teammate and leader
• 4-6 years relevant experience
• Education: Bachelor’s degree or higher in Software Engineering, Computer Science, Machine Learning, or a related field

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Sr. ML Data Engineer, Relevancy Sciences – Personalization & Loyalty Strategy (P508)

The Relevancy Sciences Team is responsible for creating relevant and personalized customer experiences for Kroger's E-commerce platform, which ranks among the top 10 ecommerce companies in the US. We generate trillions of recommendations at scale and deliver them to millions of Kroger customers daily. Our team maintains a comprehensive portfolio of machine learning solutions for search & product recommendations. We are seeking a talented and experienced Senior ML Data Engineer to join our data science team, with specialized expertise in building search and recommender systems.

Role Overview

You will architect, build, and operate the critical data infrastructure that powers our machine learning models, spanning from feature engineering to training data generation. This role serves as the bridge between ML requirements and production data systems, with ownership of feature stores, training/evaluation pipelines, and ML-specific data operations. You will enable data scientists to iterate rapidly while ensuring production-grade reliability and scalability.

What You'll Do

1. Feature Store Operations & Governance (40%)

• Own the feature request lifecycle from intake through deployment, driving reusability and maintaining a searchable feature catalog
• Design and build scalable feature pipelines that compute features from diverse sources (BigQuery, Azure Data Lake) and write to Feature Store infrastructure (Vertex AI Feature Store + BigQuery)
• Build streaming feature engineering pipelines using Apache Beam/Dataflow for real time feature computation and low-latency model serving with sub-second data freshness
• Ensure point-in-time correctness and online/offline feature consistency to prevent data leakage
• Implement drift detection, data quality monitoring, and alerting mechanisms
• Develop self-service tools and templates that enable teams to independently create features

1. Training & Evaluation Data Pipelines (30%)

• Build automated pipelines that generate ML-ready training datasets by combining features with labeled target variables
• Implement point-in-time correctness logic and sophisticated sampling strategies to ensure balanced, representative datasets
• Maintain comprehensive dataset versioning for full traceability across model versions
• Generate detailed evaluation reports with performance metrics segmented by business dimensions
• Support operations across both Azure and Vertex AI environments during platform migration

1. ML Data Operations & Reliability (20%)

• Serve as Tier 2/3 on-call responder for feature data quality incidents, diagnosing and resolving pipeline failures and performance issues
• Maintain comprehensive lineage tracking and metadata management for full data traceability
• Support regulatory compliance through proper data governance and documentation

1. Standards, Education & Collaboration (10%)

• Establish and enforce feature naming conventions, data quality thresholds, and point-in-time correctness patterns
• Conduct workshops on feature engineering best practices and provide expert guidance on feature design
• Partner with Data Scientists, ML Engineers, Data Engineering, and MLOps teams to optimize infrastructure and align with technical strategy

What We're Looking For

Required Qualifications:

• 3+ years of hands-on experience building and maintaining ML data pipelines in production environments with demonstrated expertise in scaling and reliability
• Expert-level SQL skills and advanced Python programming capabilities with experience in data processing frameworks and ML libraries
• Proven experience with cloud data platforms, with strong preference for GCP ecosystem including BigQuery, Dataflow, Vertex AI Feature Store, and associated ML services
• Deep understanding of end-to-end ML workflows including training data preparation, model evaluation methodologies, and serving infrastructure requirements
• Production operations mindset with experience in monitoring, alerting, on-call responsibilities, and meeting SLA commitments

Strongly Preferred Qualifications:

• Hands-on experience with Feature Store platforms such as Vertex AI Feature Store, Feast, Tecton, or similar enterprise solutions
• Deep knowledge of point-in-time correctness principles, temporal joins, and time-series data modeling best practices
• Multi-cloud experience with both Azure and GCP platforms, including data migration and hybrid cloud architectures
• Strong familiarity with core ML concepts including feature engineering, label creation, train/test/validation splits, and data leakage prevention
• Background spanning both analytics engineering and ML-specific data engineering with understanding of the unique requirements of each domain

Success Indicators:

• Improved Data Science Productivity:Data Scientists spend significantly less time on data preparation and infrastructure concerns, enabling more focus on model development and experimentation
• Increased Feature Reuse:Measurable increase in feature reuse across multiple models and teams, reducing redundant development effort and improving consistency
• Reliable Automation:Training and evaluation data generation processes operate reliably with minimal manual intervention and high uptime
• Efficient Incident Response:Data quality incidents are triaged quickly with clear escalation paths and rapid resolution times
• Accelerated ML Iteration:Overall ML model development and iteration velocity improves measurably across all teams using the platform

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• Build automated dashboards from scratch using Power BI and/or Tableau
• Perform statistical data analysis on large data sets, resulting in impactful insights and outcomes
• Work with a variety of clients in a variety of industries to source required data for dashboards
• Provide strategic input on data-driven decision-making and proper KPI’s
• Develop net new calculations to produce required dashboard metrics/KPI's
• Build and maintain user documentation, architecture designs, and data flow diagrams
• Solve challenging problems by utilizing analytics
• Identify opportunities to add value to the client's organization by effective use of information management
• Build relationships with key stakeholders responsible for information and performance management in client's organization
• Lead change management efforts in client’s organization

• Two (2) years of hands-on development experience with Microsoft Business Intelligence stack utilizing a variety of BI tools
• Ability to thrive in a fast-paced, dynamic, client-facing role where delivering solid work products to exceed high expectations is a measure of success
• Excellent leadership, communication, and interpersonal skills
• (Preferred) Experience in utilizing tools such as R, SAS, Python, etc.
• Strong analytic skills related to working with structured and unstructured datasets
• Build processes supporting data transformation, data structures, metadata, dependency, and workload management
• A successful history of manipulating, processing, and extracting value from large, disconnected datasets
• Ability to interface with multiple other business functions (internally and externally)
• Desire to build analytical competencies in others within the business
• Curiosity to ask questions and challenge the status quo
• Creativity to devise out-of-the-box solutions
• Ability to travel as needed to meet client requirements

• Competitive pay and bonus 
• Travel incentive bonus structure
• Flexible time off
• Investment in your growth and development
• Full health, vision, dental and life benefits
• Paid parental leave
• 3:1 charity match

At Armis, our Sales Engineers (SE) serve as the linchpin of every prospect engagement. Working closely with our prospects to demonstrate the value of the Armis agentless platform via console demonstrations, proof-of-value deployments, and targeted training sessions.

What you'll do...

Work closely with our prospects to:

• Provide virtual and in-person technical demonstrations
• Deploy proof-of-value installations
• Lead technical training sessions based on POV findings
• Support marketing activities, conferences, speaking engagements
• Consistently and cogently address our prospects needs through astute verbal and written communication skills
• Thrive in a team-oriented culture through delivering a significant individual contribution while collaborating with and strengthening teammates
• Think critically, spanning the sales process through customer support, troubleshooting, and developing new use cases for internal and external consumption.
• Develop prospect facing documentation
• Expected to travel up to 40% of the time on average (can vary by region)

Education:

• BS degrees in computer science, MIS, or equivalent experience required

Experience:

• 5+ years experience in technical positions required (SE, Pre-Sales Engineer, Solutions Architect) ideally for a Cyber Security vendor
• 5+ years of experience in customer-facing or customer support positions
• Solid understanding of networking concepts and technologies
• A demonstrated track record of taking ownership of complex initiatives and producing successful outcomes
• Experience closing complex cyber security SaaS solutions with Enterprise Customers and supporting Sales AE's / RSM's.

Knowledge in one or more of the following:

• IoT, OT, IoMT
• Wireless technologies (WLCs, Meraki, Aruba, etc.)
• Linux Operating Systems
• Virtualized environments
• Network knowledge
• Utility Scripting (Python preferred)