Starday Overview
Starday helps CPG innovation teams make better decisions, faster.
Our clients hire us to answer critical questions about where to innovate, what products to build, and which opportunities are most likely to succeed. Innovation teams already have access to enormous amounts of information including consumer research, social listening, trend reports, retail data, competitive intelligence, and internal knowledge. The challenge is turning that information into clear, defensible decisions.
Starday combines deep CPG expertise with proprietary technology to make that process faster, more systematic, and more scalable. Our technology helps experts gather, organize, synthesize, and evaluate evidence so they can spend more time on creativity, strategic thinking, and judgment.
Our goal is not to replace experts, but to scale their expertise.
Role Overview
We are looking for a Lead Data & AI Applications Engineer to build and evolve the technical systems that power Starday's innovation work.
This is a hands-on individual contributor role at the intersection of software engineering, AI, and data, with an expected mix of roughly 75% application/software engineering and 25% data science and AI.
You will build applications and services that turn Starday's data, analytical methods, and expert workflows into reliable, intuitive tools used by our team and, increasingly, our clients. You will work closely with our Data Scientist and with teammates across insights, innovation strategy, product development, and client delivery.
This is a Lead-level individual contributor role. You will not have direct reports initially but that could change based on our growth and your career objectives. In the beginning you will lead through technical ownership, architectural judgment, mentorship, and your ability to independently drive ambiguous initiatives from idea to production.
Specific Responsibilities
Build Applications & Platform Capabilities
- Design, build, and maintain applications used to conduct research, synthesize evidence, evaluate opportunities, and support innovation decisions in collaboration with Product & Delivery teams
- Turn prototypes, notebooks, and internal tools into reliable production applications
- Build APIs, backend services, data access layers, and workflows that connect Starday's datasets, analytical methods, and AI capabilities.
- Improve architecture, performance, usability, authentication, observability, and maintainability as the platform scales
- Architect workflows that can handle millions (and eventually billions) of data points while keeping latency low
Build AI-Enabled Workflows
- Develop AI features that help experts retrieve information, identify patterns, synthesize evidence, and evaluate ideas
- Work with LLMs, retrieval-augmented generation, semantic search, embeddings, structured outputs, multimodal models, and agentic workflows when appropriate
- Build evaluation approaches to understand whether AI-enabled features are accurate, useful, and reliable
- Partner with our Data Scientists to productionize models, ontologies, scoring systems, and analytical methods
Own Deployment & Engineering Quality
- Deploy and operate the systems you build in AWS
- Establish appropriate testing, CI/CD, logging, error handling, and release practices
- Improve the security, reliability, and maintainability of Starday's entire platform
- Identify recurring technical problems and build solutions that eliminate them rather than repeatedly working around them.
Your First Projects
One of Starday’s core technology goals has been to bring together disparate, organically collected data across consumer, product, and trend domains. We are now moving into the next phase: building the systems that uncover connections across those domains and make the right evidence accessible to our teams at the moment they need it.
As part of that effort, we are developing automated analysis that organizes topics using our proprietary ontology and makes them accessible through an AI-powered decision intelligence platform combining conversational interaction, data insights, source traceability, feedback loops, and self-improving workflows. After onboarding, you will take technical ownership of bringing this platform into production within our existing internal web application and into the hands of the product and delivery teams who use it to support client recommendations.
You will also play an important role in deciding what we should build next and how we should build it.
What We're Looking For
- Approximately 5+ years of professional experience across software engineering, data applications, machine learning engineering, data science, or related technical roles
- Strong software development skills, particularly in Python, with experience building maintainable production applications (using Typescript) using Claude Code & Codex
- Experience designing and deploying backend services, APIs, data-intensive applications, or internal platforms
- Experience deploying applications in AWS cloud environments
- Familiarity with modern engineering practices including testing, version control, CI/CD, monitoring, documentation, and code review
- Hands-on experience building with modern AI technologies such as LLMs, RAG, embeddings, semantic search, multimodal models, or agentic systems.
- Enough grounding in machine learning and data science to collaborate effectively with data scientists and productionize analytical methods
- Strong architectural judgment and an ability to balance speed, technical quality, and business impact
- A track record of taking ambiguous problems from stakeholder conversations through working production solutions
- Strong communication skills and an ability to work effectively with people across technical and non-technical functions
Why Join Starday
At Starday, technology is directly connected to real decisions. The systems you build will be used by people deciding where major consumer brands should innovate, which opportunities deserve investment, and what products should ultimately reach consumers.
You will join a small team where a strong engineer can have meaningful influence over our architecture, engineering practices, product strategy, and the role AI plays in the future of CPG innovation.
If you enjoy building at the intersection of software, AI, data, and real-world decision-making, we'd love to hear from you.