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 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

The AI Enablement team is building the AI foundation for 84.51° and Kroger. The AI Enablement team is composed of multiple squads, and we are looking for a Senior Agile Delivery to oversee the AI Proprietary Models + AI Hub group. Our AI Proprietary Models team creates domain specific models and associated services, while our AI Hub team maintains a centralized hub of AI information and capabilities for internal associates.

As the SENIOR AGILE DELIVERY, you'll be the orchestrator across three squads, ensuring seamless collaboration, clear visibility, and efficient delivery. You'll work closely with data scientists, researchers, engineers, and product managers to adapt Agile practices that fit the unique nature of AI and research work. Your focus will be on facilitating cross-team dependencies, managing delivery logistics, and ensuring teams have what they need to succeed. This role requires exceptional organizational skills, flexibility in approach, and the ability to thrive in an innovative environment.

RESPONSIBILITIES:

• Facilitate cross-team dependencies and alignment across three squads (two AI Proprietary Models sub-squads and one AI Hub squad), ensuring work flows smoothly and blockers are resolved quickly
• Adapt and evolve Agile practices to fit the unique workflows of data science, research, and engineering teams, moving beyond traditional sprint-based approaches where needed
• Manage and maintain Jira boards including stories, epics, and initiatives, ensuring clear visibility of progress, priorities, and team health
• Report on progress, risks, and blockers to leadership and stakeholders; escalate issues that require intervention
• Facilitate team ceremonies including stand-ups, planning, refinement, and retrospectives, ensuring clear ownership and productive outcomes
• Partner with Product Managers to ensure teams are planning the right amount of work and maintaining sustainable delivery pace
• Act as liaison across teams to successfully align work, manage dependencies, and mitigate risks
• Reduce friction and remove obstacles that slow down delivery, innovating on ways to make value delivery easier
• Champion continuous improvement, helping teams identify and execute on opportunities to enhance their ways of working

QUALIFICATIONS, SKILLS, AND EXPERIENCE:

• 2-4 years of experience as an Agile Delivery Lead, Scrum Master, or similar role supporting software engineering or data science teams
• Hands-on experience with Jira for managing backlogs, epics, stories, and reporting
• Exceptional organizational skills with proven ability to manage multiple priorities and keep teams aligned
• Strong written and verbal communication skills; ability to translate between technical and non-technical audiences
• Understanding of agile principles and practices (Scrum, Kanban) with flexibility to adapt methodologies to fit team needs
• Experience working with cross-functional teams including engineers, data scientists, product managers, and designers
• Ability to identify and resolve blockers, manage risks, and escalate appropriately
• Comfort with ambiguity and ability to remain resourceful in the face of changing priorities
• Certified Scrum Master (CSM or PSM I) preferred
• Experience in AI/ML, data science, or research environments a plus
• Bachelor's degree or equivalent experience

#LI-EB1

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

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

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).

84.51° is a retail data science, insights, and media company that helps brands grow by delivering smarter, more accountable marketing powered by Kroger’s first-party data. Kroger Precision Marketing (KPM) is our commercial arm, enabling brands to connect with customers through insights, incentives, and media.

Role Summary

Kroger Precision Marketing (KPM) recently launched a new AI Platform team to help product teams bring safe, scalable AI to market across our brand-facing platforms. We do that by (1) consulting on standards and guardrails; (2) accelerating reusable tools and early features, then transitioning long-term ownership to product teams; and (3) operationalizing a repeatable way to ship, monitor, and improve AI at scale.

As a Product Manager on this team, you will work alongside other PMs and a Product Director who sets the overall vision and strategy. You will own end-to-end initiatives that span multiple projects and features, from discovery through delivery and adoption, and you will be accountable for the business outcomes and KPIs those initiatives drive. You will also build and evolve reusable AI tooling for other teams, and consult with those teams to align strategies, reduce duplication, and ensure we ship AI consistently and safely across KPM’s brand-facing platforms.

Key Responsibilities

• Build the game plan: translate the AI portfolio vision into a clear roadmap for your initiatives
• Pick the right bets: focus the roadmap on the highest-impact work by weighing impact, effort, and risk, and deprioritizing the rest
• Stay ahead of the market: stay current on AI trends, vendors, and competitor moves, and use those insights to inform recommendations and influence our strategy
• Have a point of view, stay curious: form a clear perspective, seek input early, and adjust quickly when evidence points to a better approach
• Get close to users: partner with Experience Design to run discovery and define what we will build, why it matters, and why now
• Ship with momentum: drive delivery with Agile Delivery, Data Science, and Engineering by managing scope, dependencies, risks, tradeoffs, and timelines
• Prove and improve: measure outcomes against business KPIs, collect user and stakeholder feedback, and iterate based on real signal (qualitative and quantitative)
• Make it stick: support rollout and adoption, then hand off with clear enablement and accountability
• Scale the capabilities: own reusable AI capabilities, including skills, patterns, and tooling, that help teams across the company build smarter and faster
• Tell the story: communicate progress, tradeoffs, and decisions with clarity, and raise risks early with context and options
• Be the go-to partner: earn trust through strong follow-through, clear communication, and reliable decision-making, while balancing confidence with humility

Minimum Qualifications

• Product management: 3–5 years of product management experience
• AI/ML delivery: familiarity with the AI/ML product lifecycle, including data readiness, model development, deployment, monitoring, and governance
• GenAI fundamentals: working knowledge of prompting, retrieval-augmented generation (RAG), agent patterns and skills, and quality and safety evaluation
• Roadmap: ability to set priorities and drive execution independently
• Decision-making: ability to make calls, clarify tradeoffs, and create clarity in ambiguity
• Delivery: experience partnering with Experience Design, Data Science, Engineering, and Agile Delivery
• Communication: ability to translate between technical and business teams, manage stakeholders, and raise risks early with context and options
• Metrics: ability to define success, measure outcomes, and iterate based on real signal
• Leadership: a humble, direct leadership style, comfortable saying “I don’t know,” and confident leading toward an answer
• Collaboration: ability to move fast within security, governance, and complex stakeholder environments

Preferred Qualifications

• B2B platform: experience building products for large, diverse internal or external user bases
• Industry: familiarity with retail analytics, retail media, adtech, and data-driven marketing platforms
• Technical fluency: background in engineering, data science, analytics, or a highly technical product area, with the ability to go deep on architecture and delivery tradeoffs
• Experimentation and measurement: product analytics experience defining success metrics, selecting the right measures for the job (for example, using Google’s HEART framework), and running experiments to quantify user and business impact

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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

#LI-SSS

#LI-Remote

Lead Technical Product Manager – Agent Platform 

LOCATION: Cincinnati / Chicago (P4476) 

SUMMARY:  

The AI Enablement team at 84.51° is seeking a Lead Product Manager for its Agent Platform team. This team is responsible for architecting, implementing, maintaining, and supporting the use of the agentic foundation of the Kroger enterprise. 

The Lead Product Manager will discover, prioritize, plan the implementation of the agent platform – this could include: a control layer consisting of agent, MCP, eval, and prompt registries; evaluation and monitoring tools; and pro-code, low-code, and no-code development capabilities. The role will partner closely with engineering and data science leads to shape the roadmap, translate business and technical needs into clear requirements, and ensure the delivery of high-value, enterprise-grade capabilities that reduce time-to-value, improve quality and reliability, and promote safe, compliant use of agentic systems. 
 

RESPONSIBILITIES: 

• Own product discovery and roadmap for the managed agent platform 
• Maintain a current roadmap and communicate trade-offs, dependencies, and timelines to stakeholders and delivery teams 

• Translate business goals, user needs, and technical constraints into product requirements and acceptance criteria with a clear definition of done 

• Partner with the Agentic Foundations leadership, as well as engineering and data science leads, to plan quarters/cycles/sprints and ensure efficient, predictable delivery 

• Define and evolve core agentic platform capabilities, including: 

• Registries (agent/MCP/scorer/prompt), templates, and pattern libraries 

• Agent development and monitoring tools, including evaluation frameworks and observability 

• Integration with data and API layers and pro-code agent frameworks 

• Integration with enterprise AIOps/MLOps, CI/CD, and governance workflows 

• Facilitate user research and testing to understand developer and business user workflows; validate usability, safety, reliability, and performance 

• Analyze product usage and operational data to inform prioritization, measure value, and guide iteration 

• Drive adoption across customer teams through documentation, enablement, demos, and feedback loops; remove friction points and champion best practice 

• Ensure alignment with enterprise strategies for scale, reliability, safety, compliance, and cost-efficiency 

• Manage progress toward objectives; proactively surface risks, blocks, and cross-team dependencies; coordinate mitigation plans 

• Develop strong internal and external stakeholder relationships; influence and drive change in ambiguous, evolving environments 

• Communicate realized value and outcomes, including usage, adoption, productivity improvements, and risk reduction 

QUALIFICATIONS, SKILLS, AND EXPERIENCE:  

• Professional experience in leading enterprise AI, ML, or data platforms 

• Professional experience in a product/software development team  

• Professional experience in managing technical and business stakeholders  

• Professional experience in ambiguous environments  

• Skilled in a general technical acumen, able to efficiently converse with software engineers and AI engineers and understand their development processes  

• Skilled in managing cross-functional technical 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  

• 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  

• Skilled in quickly flexing between technical and business stakeholder conversations, adapting to a variety of audiences  

• 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

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

SUMMARY:

We are seeking a dynamic, hands-on, strategic and highly collaborative Vice President, Strategic initiatives to lead cross-functional initiatives that drive technological innovation and operational excellence across the firm. This role will serve as a bridge between software engineering, infrastructure, marketing, financial services and leadership team, with a strong focus on delivering value through solutions that scale. 

You’ll be the architect and implementor of transformative projects — from AI-driven automations to system integrations supporting client acquisition and experience. This is a roll-up-your-sleeves role for a technically proficient leader with exceptional project vision, execution discipline, and an explorative mindset. 

This is an full time Exempt position with a salary range of $150-$180K annual salary. This position will be in our Folsom, CA, Addison, TX, Cincinnati, OH office or working remote. 

Key Responsibilities 

• Project Leadership & Execution 

• Lead high-impact, cross-disciplinary special projects across engineering, marketing tech, operations, and M&A needs. 

• Serve as the strategic and technical owner of initiatives involving AI, automation, strategic CRM enhancements or new tool selection, and marketing enablement tools. 

• Be a vocal champion for AI progress within the firm, partnering with the AI council on strategy and execution 

• Actively seek out meaningful, scalable use cases within the business where AI can unlock efficiency, insights, or innovation. 

• Work closely with the financial services group and Analytics team. 

• Technical Innovation & Hands-On Development 

• Evaluate, prototype, and implement modern technologies (AI/ML, automation frameworks, low-code platforms) including automation. 

• Work hands-on when necessary — writing proof-of-concept code, creating technical documentation, or leading architecture design. 

• Stay current on AI trends and capabilities enough to confidently assess what’s possible, what’s hype, and how to frame solutions that are both ambitious and achievable. 

• Platform Strategy & Integration 

• Find creative ideas to build and support data migration and conversion efforts related to acquisitions and business process optimization. 

• Have a strong focus of efficiency, scalability, security and adherence to compliance standards. 

•  Partner with Marketing, Service, advisors and Client Experience teams to co-implement technology-backed growth strategies. 

• Infrastructure & Scaling 

• Support the infrastructure team to select and deploy internal and client-facing tools that is scalable, secure, and efficient.  

• Leverage third party service providers and offshore vendors for expertise. 

• Research and find tools suited best for the business and perform POC to vet solutions for enhanced client experience and associate efficiency. 

Essential Skills & Qualifications 

Technical & Functional 

• Strong experience in software engineering and architecture (e.g., full-stack development, APIs, system integrations), project management and business analysis. 

• Expertise in: 

• Salesforce FSC (Financial Services Cloud) preferred. 

• HubSpot, Regal.io or other dialers, Tamarac or other Portfolio accounting systems 

• Data transformation/migration tools, Synapse or Microsoft Fabric data systems 

• AI/ML frameworks (e.g., OpenAI, StackAI, RAG frameworks) 

• Workflow automation (Zapier, Mulesoft, custom API integrations) 

Strategic & Operational 

• Proven track record of leading transformative cross-functional projects. 

• Experience supporting technology needs during mergers and acquisitions, especially data conversion and onboarding. 

• Deep understanding of RIA or financial services business is mandatory. 

Leadership & Collaboration 

• Highly communicative and capable of translating complex technology into business value. 

• Leadership experience in matrixed environments — able to influence without direct authority. 

• Curiosity-driven and comfortable navigating ambiguity. 

Preferred Background 

• Minimum bachelor’s in Computer Science, Engineering, or related field. 

• 10+ years of experience in software or systems engineering with a minimum of 3 years in a high growth RIA in a senior role 

• 5+ years experience in a similar role implementing transformative technical advancements.