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.

THE ROLE:

Are you passionate about driving innovation in the data storage industry? Are you skilled in crafting technical solutions that exceed customer expectations? If so, we have an exciting opportunity for you! Everpure (formerly Pure Storage), a leader in the data storage and flash technology space, is seeking a talented and motivated Senior Pre-Sales Systems Engineer to join our dynamic team. 

As a Senior Pre-Sales Systems Engineer, you will play a crucial role in understanding our customers' unique challenges and tailoring Everpure solutions to meet their specific needs. Collaborating closely with the sales team, you will act as a technical expert during the sales process, helping to showcase the value of our products and services.

The selected candidate must reside in the Cincinnati/Dayton area.

WHAT YOU’LL DO:

• Develop an exhaustive understanding of what drives a customer’s business and what motivates their decision making
• Connect the dots from technology solutions, inclusive of the Everpure portfolio and others from the ecosystem, to measurable customer business outcomes
• Partner closely with account managers, specialists and channel partners to create a seamless and holistic customer experience and strategy to drive revenue growth and net new business
• Delight customers and teammates with your technical leadership and domain expertise on storage products, distributed storage architectures, file systems, and competitive storage offerings in the DAS, NAS and SAN product spaces
• Take control of evaluations,  benchmarks and system configurations
• Build and deliver technical product and architecture presentations with vigor to customers and lock in the technical win with clients and prospective accounts
• Capture requirements and translate Customer’s business needs into innovative solutions to accelerate their growth and capacity
• Seek out and spur new opportunities for interoperability, functional, and performance testing/validation
• Promote mutual roadmap and planning exchanges
• Liaise with product and technical marketing to produce materials (i.e. whitepaper, web presentations) that support overall alliance plans and objectives
• Stay current with the competition and ensure that materials accurately reflect the latest, differentiated solution positioning
• Move with market trends and competitive landscape to promote thought leadership within our organization
• Lead by example living the Everpure Values:  Persistence, Creativity, Teamwork, Ownership and Customer-first  

WHAT YOU BRING:

• Pre-sales experience is required
• 5 or more years of relevant experience, mixed among technology, design, and communications required. Experience supporting the sales of enterprise storage, networking, systems, cloud, or software to enterprise accounts preferred
• Deep understanding of the architecture, design and implementation of multi-tiered client/server and web-based computing solutions
• Must have a familiarity with modern web architecture a plus (LAMP stack, scale-out vs scale-up architectures, AWS well-architected framework, microservices architecture)
• Prior experience in targeting new prospects and converting them into clients
• Contribute significant portions and/or lead responses to RFPs, RFQs and RFIs
• Superior knowledge of current and emerging storage architectures (FC, iSCSI, NAS, OSD, SAN)
• Previous experience with Linux, NFS file systems and Linux distributed network environment
• Installation/configuration of distributed computing, multiprocessing, virtual memory subsystem, storage subsystems architecture, shared memory architectures, cache architectures, windowing systems
• Strong knowledge of digital transformation to a Cloud Native architecture, On-Prem, Public Cloud, Provisioning Automation, and Containers
• Knowledge of VMware, Local Area Networking, Ethernet, TCP/IP and general networking
• Familiarity with AWS, Azure, GCP, containers, k8s and microservices architectures a plus
• Curiosity and passion around technology and explaining and showing new technology platforms and concepts to customers
• Familiarity with storage-intensive applications and their requirements such as structured databases (SQL, Oracle) is highly desirable
• Excellent verbal and written interpersonal skills

#LI-REMOTE

#LI-JL4

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)

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.

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

Lead Technical Product Manager(G3) 

LOCATION: Chicago/Cincinnati 

COMPANY OVERVIEW: 

84.51° knows customers, and we know how to connect you.  

Using a sophisticated, proprietary suite of tools and technology, we turn customer data into actionable knowledge. With unparalleled customer data and predictive analytics capabilities, we deliver personalized marketing strategies and ensure the best experience for customers of Kroger and more than 300 consumer-packaged-goods companies. We put the customer at the center of everything we do, resulting in a more dynamic, informed and personal approach to driving customer loyalty. 

SUMMARY:  

The AI Enablement team builds foundational AI capabilities that transform Kroger and 84.51, including better solutions and outcomes for our shoppers and our associates. AI Gateway is a cross-functional team within AI Enablement responsible for the primary AI model and API infrastructure that powers these solutions and democratizes access to AI across the org. As the Product Manager for this team, you will work closely with the Director of Product, Tech Leads for the AI Gateway, and cross-functional design and development teams. 

The LEAD PRODUCT MANAGER is the chief navigator, business champion, and team linguist that is accountable for setting team priorities and maximizing the value of the product results from the work of the development team. You own the details of the business and technical value delivered at the team level. You translate business requirements into product requirements to ensure that the product delivers on user needs. You own the measurement of the value delivered and other metrics for your product. This role requires excellent organizational and communication skills, technical acumen, and artificial intelligence domain knowledge. 

RESPONSIBILITIES:  

• Drive business value for the team by prioritizing and ordering product backlog items based on the product roadmap, inclusive of product, engineering, UX and data science roadmaps. 
• Experienced in managing multiple teams’ product backlogs in parallel and ensuring they’re transparent, visible and clearly communicated.
• Partner with cross-functional engineering, UX and data science peers to translate business desires/requirements into effective features and stories that are ready for development.
• Outlines clear acceptance criteria, to clearly communicate the definition of “done”.
• Partner with external contractors or technical support to ensure the delivery of the scope of work, within the agreed timeline, and in accordance to the stated acceptance criteria.
• Deep understanding of the business domain, stakeholders, business processes and constraints in which your product(s) play 
• Deep understanding of customers/users’ problems, how they think and operate and the platforms/technology they use. Ability to become familiar with new technology, business domains, and/or analytical practices that impact your product(s). 
• Understand and communicate organization objectives, strategies and solution needs to the team to facilitate results (where collaborative/as colleague)
• Manage and communicate dependencies and risks.
• Stakeholder management – experienced in building and managing internal and external stakeholder relationships to influence and drive change.
• Experienced level knowledge in the development and use of product data to influence product decisions/roadmap – both quantitative and qualitative.
• Clearly communicate the value of the work being delivered

QUALIFICATIONS, SKILLS, AND EXPERIENCE:  

• Professional work experience in artificial intelligence / Generative AI applications.
• Experience managing and/or developing an API-based product or developer tooling.
• Experience managing and/or developing cloud-based solutions in Azure or Google Cloud.
• Experience scaling apps or systems to meet high-availability and resiliency requirements for critical internal and customer facing solutions.
  • Experience managing and/or working on a team that deploys AI/ML models in cloud-based settings.
  • Technical acumen – possess the foundational technical knowledge needed to communicate with the technical team, understand blockers/trade-offs, and incorporate technical needs in the roadmap.
  • Experience navigating corporate governance processes including Security, Cloud, Privacy, Data Sharing, and Legal.
• Skilled in managing cross-functional software development teams in an agile environment
• Skilled in managing business priorities against design/user needs while delivering against product roadmaps
• Skilled in managing end-to-end software product development.
• Stakeholder management skills – experienced in building and managing stakeholder relationships to influence and drive change.
• Problem solving, critical thinking and analytical skills
• Planning, organizational and time management skills
• Comfort with ambiguity – remains confident, positive and resourceful in the face of ambiguity and unexpected results; recovers quickly from setbacks.
• Exhibits qualities of and have proven to be a great teammate
• Verbal and written communication skills, ability to translate between business and technical
• 4-6 years relevant experience
• Education: Bachelor’s degree or equivalent experience

ADDITIONAL SKILLS OF INTEREST (NOT REQUIRED) 

• Prior experience as a software engineer or Technical Product Manager – many of our customers are software engineers and data scientists.
• Experience leveraging various Generative AI chat tools (ie M365 Copilot, ChatGPT, Gemini, Claude) to simplify your life, work, or otherwise automate processes and accomplish previously impossible things. 
• Experience developing AI Agents using an agent builder or agent framework.
• Experience developing or using MCP servers.
• Experience using coding agents (ie Claude Code, Codex, Gemini CLI, Github Copilot).

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

#LI-SSS

#LI-Remote

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

#LI-SSS

#LI-Remote

• Create and maintain optimal data pipeline architecture
• Assemble large, complex data sets that meet functional / non-functional business requirements
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources
• Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency, and other key business performance metrics
• Work with stakeholders including the Executive, Product, Data, and Design teams to assist with data-related technical issues and support their data infrastructure needs
• Define project requirements by identifying project milestones, phases, and deliverables
• Execute project plan, report progress, identify and resolve problems, and recommend further actions
• Delegate tasks to appropriate resources as project requirements dictate
• Design, develop, and deliver audience training and adoption methods and materials

• Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases. Databricks and DBT experience is a plus
• Experience building and optimizing data pipelines, architectures, and data sets
• Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement
• 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

• Create and maintain optimal data pipeline architecture
• Assemble large, complex data sets that meet functional / non-functional business requirements
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources
• Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency, and other key business performance metrics
• Work with stakeholders including the Executive, Product, Data, and Design teams to assist with data-related technical issues and support their data infrastructure needs
• Define project requirements by identifying project milestones, phases, and deliverables
• Execute project plan, report progress, identify and resolve problems, and recommend further actions
• Delegate tasks to appropriate resources as project requirements dictate
• Design, develop, and deliver audience training and adoption methods and materials

• Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases. Databricks and DBT experience is a plus
• Experience building and optimizing data pipelines, architectures, and data sets
• Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement
• 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

• Lead and facilitate critical thinking within a manufacturing or operations environment to bring new perspectives and ideas to reduce waste and improve efficiency
• Reduce machine downtime by implementing new changeover techniques
• Promote process improvement by using best practices within manufacturing methods, labor utilization standards, and cost analysis systems to gain efficient staff and facility utilization
• Analyze production costs and implement cost saving methods
• Analyze statistical data and product specifications to determine standards and establish quality and reliability objectives of finished product
• Confer with clients, vendors, staff, and management personnel regarding purchases, product and production specifications, manufacturing capabilities, or project status
• Review production schedules, engineering specifications, orders, and related information to obtain knowledge of manufacturing methods, procedures, and activities
• Study operations sequence, material flow, functional statements, organization charts, and project information to determine worker functions and responsibilities
• Regulate and alter workflow schedules according to established manufacturing sequences and lead times to expedite production operations
• Roll out best in class maintenance and planning processes with client leaders
• Support strategy on capital expansion and planning
• Travel as needed to support client sites

• Experience in an Industrial Engineer role
• Ability to use data and statistical analysis to analyze and improve processes
• 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

• 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)