Role Description We are looking for an Applied AI Engineer to help build and expand AI-powered product features across our platform, with an initial focus on enhancing our AI Coach experience. This role is ideal for an engineer who enjoys the practical application of generative AI in production environments and works closely with product managers and engineers to translate ideas into production-ready features for customers. You will combine Python development, prompt design, and structured data work to deliver user-facing AI functionality. This is an opportunity to work on high-impact AI features in a real-world fintech environment. What You’ll Do - Build and enhance AI-powered product features in collaboration with product and engineering teams - Write and refine prompts to improve response quality and feature performance - Develop Python-based services and APIs supporting AI workflows - Work with structured data in PostgreSQL and vector-based data systems supporting AI applications - Contribute to feature implementation in FastAPI-based systems - Use AI-assisted development tools to accelerate engineering productivity and experimentation - Participate in technical discussions around feature design and implementation What Success Looks Like - Contribute meaningfully to the delivery of AI-powered product features within your first 60-90 days - Improve usability and quality of AI-generated capabilities - Contribute effectively within sprint-based engineering delivery - Demonstrate strong technical judgment in balancing speed, quality, reliability, and maintainability Qualifications - When applying, please include a brief description of one AI-powered feature, service, or system you helped build or support in production. - 3+ years of software engineering experience - Strong Python development experience - Proven proficiency with AI-powered coding tools (Anthropic's Claude Code preferred) - Experience building backend services or APIs - Experience working with LLM APIs, generative AI services, or AI-enabled capabilities in applications - Strong problem-solving and debugging skills - Ability to collaborate effectively in a cross-functional team Nice to Have - Experience with FastAPI or similar frameworks - Familiarity with prompt evaluation or LLM testing approaches - Experience integrating AI into production SaaS platforms - Experience working in fintech or B2B SaaS Benefits - Build meaningful technology that helps people improve their financial lives - Work on practical AI applications deployed in a live fintech product - Collaborate in a remote-first environment with experienced product and engineering leaders - Competitive compensation, benefits, and equity Compensation The estimated annual base salary range for this role is $125,000 to $155,000, depending on qualifications, experience, and location. This role is also eligible for: - Annual performance bonus - Equity participation - Comprehensive benefits package Actual compensation will be determined based on relevant qualifications, skills, experience, and geographic location. Equal Opportunity Employer BrightPlan is proud to be an equal opportunity employer and to consider qualified applicants without regard to race, color, religion, sex, national origin, ancestry, age, genetic information, sexual orientation, gender identity, marital or family status, veteran status, medical condition or disability.

Role Description We are looking for a Senior Applied AI Engineer to help design, build, and scale the systems that power AI across the BrightPlan platform. This role will play an important part in shaping the evolution of AI systems within BrightPlan’s product architecture. - Focus on developing reliable, scalable infrastructure and frameworks for LLM-powered applications. - Work closely with the CTO to help shape technical decisions around AI architecture, model usage, and system evolution. - Own complex technical problems and build systems that make production AI reliable and scalable. - Opportunity to have significant technical impact in a real-world fintech environment. What You’ll Do - Design and implement scalable AI services and supporting infrastructure that enable AI-powered product capabilities across the platform. - Develop solutions for evaluating and improving LLM output quality. - Build frameworks and tooling that support AI feature development across the engineering team. - Develop and maintain systems that support model tuning, evaluation, and optimization. - Contribute directly to deployment and operational reliability of AI services in production environments. - Optimize AI services for latency, cost efficiency, and reliability. - Partner with the CTO to evaluate emerging AI capabilities and recommend technical approaches for model usage, architecture, and system design. - Provide technical guidance to engineers building AI-powered features and help establish effective development patterns and engineering best practices. - Contribute to technical architecture discussions related to AI systems and platform capabilities. What Success Looks Like - Contribute meaningfully to establishing reliable systems supporting AI-powered product features within your first 90 days. - Improve the performance, consistency, and reliability of AI-generated outputs. - Enable faster experimentation and iteration for AI product development. - Help establish development patterns and technical practices that enable other engineers to build AI-powered features more effectively. - Demonstrate strong technical leadership and ownership of AI system design and implementation. Qualifications - 5+ years of software engineering experience, including strong backend or systems development experience. - Strong Python development experience. - Experience designing and building backend services or distributed systems. - Experience integrating LLM APIs, generative AI services, or AI-enabled capabilities into production systems. - Experience evaluating or improving AI model performance in production environments. - Strong problem-solving and systems design skills. - Ability to collaborate effectively in a cross-functional team. Nice to Have - Experience with FastAPI or similar frameworks. - Experience with model fine-tuning, retrieval-augmented generation (RAG), prompt evaluation, or LLM evaluation methods. - Experience building internal tooling or infrastructure supporting AI applications. - Experience working with vector databases or AI data pipelines. - Experience working in fintech or B2B SaaS environments. Benefits - Build meaningful technology that helps people improve their financial lives. - Work on practical AI applications deployed in a live fintech product. - Collaborate in a remote-first environment with experienced product and engineering leaders. - Competitive compensation, benefits, and equity. Compensation - The estimated annual base salary range for this role is $160,000 to $195,000, depending on qualifications, experience, and location. - This role is also eligible for: - Annual performance bonus. - Equity participation. - Comprehensive benefits package. - Actual compensation will be determined based on relevant qualifications, skills, experience, and geographic location.

Title: Staff AI Engineer Location: Birmingham, AL Minneapolis, MN San Francisco, CA Job Description: Impact We're hiring a Staff AI Engineer to build product features powered by modern AI models. You'll work across our Next.js/React frontend and Go backend services to ship AI-enabled capabilities that are reliable, measurable, and valuable to the business. You'll be leading projects and mentoring engineers in the best practices of software development. This role is ideal for a developer who can ship end-to-end features and is excited to leverage AI tools in their daily workflow (for research, prototyping, testing, and coding) while maintaining strong engineering quality. We do not expect you to be a machine learning researcher. We expect you to be a curious, pragmatic engineer who is excited to build customer facing capabilities. What You'll Need to Be Successful Key Responsibilities - AI Product Development - Build & Integrate: Design and implement full-stack features that utilize LLMs (OpenAI, Anthropic, Gemini) to solve user problems. You will build "Generative UI" elements where the AI renders interactive UI components. - MCP Ecosystem & Tooling: Build and maintain Model Context Protocol (MCP) servers to expose internal databases, APIs, and business logic as tools for LLMs. - Streaming Interfaces: Using tools such as Google's Agent Development Kit to build low-latency interfaces that stream text to the client, ensuring a responsive user experience even with slow models. - Roadmap Ownership: Leading a team of developers to build new features on the web and mobile experience. Designing solutions and driving consensus between different teams. - Backend Systems & Orchestration - Golang Development: Write robust, high-performance Go code to orchestrate AI services. You will use goroutines to manage concurrent agent execution and handle long-running third-party API calls efficiently. - API Design: Design and implement RESTful and gRPC APIs that serve as the interface between our frontend and the AI models. - Event-Driven Architecture: Collaborate on integrating Kafka and Redis to build asynchronous message processing pipelines. You will help decouple AI agents, allowing them to communicate via events rather than direct calls. - Observability: Ensuring dashboards are set up for monitoring services to help debug issues during on-call incidents troubleshooting. - AI-Assisted Engineering (The "AI-Enhanced" Workflow) - Tool Utilization: Actively use AI coding assistants (e.g., GitHub Copilot, Cursor, etc.) to accelerate boilerplate code generation, unit testing, and documentation. You will be expected to use these tools to multiply your output. - Code Review & Debugging: Critically evaluate and debug AI-generated code. You are the gatekeeper of quality; you must understand every line of code committed, ensuring it meets security and performance standards. You will fix errors in code logic. - Prompt Engineering & Evals: Iteratively refine system prompts to ensure consistent, safe, and high-quality model outputs. You will write automated "Evals" to test the AI's performance against regression. Required Qualifications - Experience: 8-10 years of professional software engineering experience. Core Stack: - GoLang: Practical experience building backend services or APIs in Go. Understanding of goroutines, channels, structs, and Go modules. - JavaScript/TypeScript: Proficiency with React and the Next.js ecosystem (App Router, Components, Hooks, etc.). AI/LLM Familiarity: - Experience integrating LLM APIs (OpenAI, Anthropic, Gemini) into applications. - Design and implement tools that allow AI models to interact securely with our backend services, ensuring the LLM has the right context to perform tasks. - Familiarity with orchestration concepts (Google's ADK, Vercel AI SDK, or custom orchestration). - Database Literacy: Comfortable writing SQL queries and interacting with relational databases (Postgres preferred). - Engineering Best Practices: Experience with Git version control, CI/CD basics, and writing unit tests. "Nice-to-Have" Skills (The Differentiators) - Mobile Development: Experience with React Native or Expo. Ability to deploy AI features to mobile devices and understand the constraints of mobile networks. - Advanced Data Infrastructure: Familiarity with Apache Kafka for event streaming or Redis for caching. - DevOps/Cloud: Exposure to Docker, Kubernetes, and AWS/GCP services. Pay Range: $95,800 - $180,000 Please note that the salary range above is a guideline, and individual total compensation will vary based on factors such as qualifications, skill level, competencies, and work location. Skills & Education This list includes key skills used in this job but is not inclusive of all skills needed for the role. Please see any required education below. AI Programming, Application Programming Interface (API), Backend Systems, Go Programming Language Bachelor's Degree or equivalent experience | Required Work Arrangement Shipt considers candidates located near a Shipt office or workspace in Birmingham, San Francisco, or Minneapolis to be hybrid, which means that they have the flexibility to work from home (with leader approval) or at a Shipt office in order to facilitate the ability to innovate, collaborate, and spark team connections. In-office expectations will vary by role and leader. Certain roles may require in-office presence on a full-time basis. Please work with your recruiter to learn more about the classification of this role. About Shipt Shipt is a retail tech company that connects people to reliable, high-quality delivery with a personal touch. Shipt connects customers to the things they want from the stores they love, retail businesses to more satisfied customers, and workers to new earning opportunities. At Shipt, we aim to put our team first to boost a sense of belonging, spark opportunities for growth, provide unique benefits and commit to giving back to our communities in ways that make life better, both personally and professionally. We understand that our service, our culture, and our connection to our communities are only made better by every single person who shows up to work here every day. Learn More. Shipt is an independently operated, wholly owned subsidiary of Target Corporation and available in more than 5,000 U.S. cities. Shipt was founded and is headquartered in Birmingham, Alabama. For more information, please visit Shipt's company site at Shipt.com. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, color, national origin, ethnicity, religion or religious belief, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, military or veteran status, disability, or any other characteristic protected by law. Employees (and eligible family members) are covered by medical, dental, vision and more. Employees may enroll in our company’s 401k plan. Employees will also be eligible to receive discretionary vacation for exempt team members, paid holidays throughout the calendar year and paid sick leave. Other compensation includes eligibility for an annual bonus and the potential for restricted stock units based on role.

• Spend around 80% of the role providing technical guidance to client and consulting teams on AI-assisted software engineering, developer productivity, architecture, microservices, build processes, CI/CD, testing, security, and engineering workflows. • Advise and coach engineering teams on modern software engineering practices and adoption of AI tools such as Claude Code, Cursor, Codex, or GitHub Copilot. • Define technical approaches for product architecture, data flows, integrations, and build processes. • Spend around 20% of the role on hands-on architecture and delivery, including designing, developing, and documenting AI applications aligned to business outcomes. • Build or support LLM-powered applications, RAG pipelines, and AI agent systems. • Translate business requirements into technical solutions and contribute to implementation, testing, and code reviews.