Profitmind Jobs in Usa
5 positions found
Profitmind is building the intelligence behind how retailers make pricing and merchandising decisions. Today, many of these decisions are still driven by spreadsheets, rigid rules, and manual judgment, even at the largest brands.
Our platform turns complex data such as sales, inventory, and competitive signals into clear, explainable recommendations merchants can trust. Our platform focuses on impact, helping retailers improve margin, inventory health, and decision quality at scale.
Based in Pittsburgh, we’re a fast-growing startup with real customers. Profitmind is backed by a recent strategic investment from Accenture, and scaling its agentic AI platform to power decision-making for some of the world’s largest retailers.
About the role:
We're seeking a talented Senior Data Engineer to build and scale the data infrastructure that powers our retail technology platform. As a key member of our early-stage team, you'll design and implement robust data pipelines, establish best practices for data engineering, and enable data-driven decision making across the organization. This is a unique opportunity to shape the data foundation of a growing startup and work with cutting-edge technologies in both batch and streaming data processing.
What you’ll do:
- Design and implement scalable data pipelines for both batch and streaming workloads using Python and Spark
- Build and maintain cloud-native data infrastructure to support our retail analytics and operational needs
- Develop real-time streaming solutions to process transaction, inventory, and operational data
- Develop AI agents to automate operations
- Implement data quality validation and monitoring to ensure reliability across our data ecosystem
- Establish DataOps best practices and automation as we scale our data infrastructure Own data security and privacy compliance as we handle sensitive customer and business data
- Collaborate closely with product, engineering, and business teams to understand data requirements and deliver solutions
- Mentor team members and contribute to building a strong data engineering culture
What we’re looking for:
- 5+ years of hands-on data engineering experience
- Strong proficiency in Python for data processing and pipeline development
- Production experience with Apache Spark for large-scale data processing
- Hands-on experience with at least one major cloud platform (AWS, GCP, or Azure)
- Proven track record implementing both batch and streaming data pipelines
- Deep understanding of SQL and modern data warehouse technologies
- Strong knowledge of data modeling, ETL/ELT patterns, and workflow orchestration Experience with distributed systems and cloud infrastructure
- Excellent problem-solving and analytical skills
- Strong communication skills with ability to translate business needs into technical solutions Thrives in fast-paced, early-stage startup environments with changing priorities
Nice to have:
- Experience in retail tech, e-commerce, or similar enterprise systems
- Expertise with real-time processing frameworks like Kafka, Kinesis, or Flink
- Proficiency with Python data handling libraries (pandas, NumPy, polars)
- Knowledge of data quality and observability platforms
- Understanding of event-driven architectures, medallion architectures, and CDC patterns
- Previous experience at an early-stage startup or building data infrastructure from scratch
- Background working with multi-tenant SaaS platforms or enterprise analytics systems
- Experience with container orchestration (Docker, Kubernetes)
- Knowledge of DataOps and MLOps best practices
Apply today to join a small, senior team working on problems that sit at the core of how global retailers operate.
Profitmind is building the intelligence behind how retailers make pricing and merchandising decisions. Today, many of these decisions are still driven by spreadsheets, rigid rules, and manual judgment, even at the largest brands.
Our platform turns complex data such as sales, inventory, and competitive signals into clear, explainable recommendations merchants can trust. Our platform focuses on impact, helping retailers improve margin, inventory health, and decision quality at scale.
Based in Pittsburgh, Profitmind is backed by a recent strategic investment from Accenture, and scaling its agentic AI platform to power decision-making for some of the world’s largest retailers.
About the role:
We are seeking a Machine Learning Engineer who understands the heartbeat of retail. In this role, you will build the intelligence that helps major retailers make critical merchandising decisions, balancing profit, revenue, and inventory health.
You will sit at the intersection of ML Engineering, Retail Strategy, and Data Science. Your work will power the "brain" of our platform, transforming raw sales data and competitive signals into actionable pricing strategies and clear insights for merchants and buyers.
What you’ll do:
- Design and deploy models specifically for retail challenges, such as demand forecasting, price elasticity at the SKU level, seasonality detection, and markdown optimization.
- Evolve our Python-based optimization engine to handle complex retail constraints (e.g., maintaining brand standards, psychological price points, and inventory sell-through targets).
- Engineer systems that explain the "why" behind a price change. You will translate model outputs into merchant-friendly insights (e.g., "We recommend a markdown here because competitor X dropped price and inventory depth is high").
- Develop logic to optimize products across their entire lifecycle—from initial price setting to promotional strategies and final clearance.
- Build robust data pipelines to ingest and process diverse retail datasets, including POS transactions, competitor scraping, and inventory feeds.
- Work closely with product managers to understand the needs of category managers and pricing analysts, ensuring our algorithms solve real-world merchandising pain points.
What we’re looking for:
- 3+ years of experience building production ML systems using Python, Scikit-learn, or PyTorch, with a focus on regression and time-series forecasting.
- A strong understanding of (or deep interest in) retail mechanics—how inventory turns, gross margin, and sell-through rates drive business success.
- Familiarity with mathematical optimization techniques and how to apply them to business constraints (e.g., linear programming, constraint satisfaction).
- Expert SQL skills and ability to model complex data relationships (e.g., parent-child product hierarchies, store clusters).
- The ability to look at an optimization result and explain the business logic behind it. You can debug not just code, but the retail logic.
- Bachelor’s degree in Computer Science, Data Science, Machine Learning, Mathematics, or a related technical field.
Nice to have:
- Master’s degree in Artificial Intelligence, Computer Science, Operations Research, or Statistics.
- Experience in Retail Analytics, E-commerce, Supply Chain, or Revenue Management.
- Familiarity with "Explainable AI" (XAI) tools to make black-box models transparent to business users.
- Experience handling sparse data or cold-start problems (e.g., pricing new products with no history).
Profitmind is building the intelligence behind how retailers make pricing and merchandising decisions. Today, many of these decisions are still driven by spreadsheets, rigid rules, and manual judgment, even at the largest brands.
Our platform turns complex data such as sales, inventory, and competitive signals into clear, explainable recommendations merchants can trust. Our platform focuses on impact, helping retailers improve margin, inventory health, and decision quality at scale.
Based in Pittsburgh, we’re a fast-growing startup with real customers. Profitmind is backed by a recent strategic investment from Accenture, and scaling its agentic AI platform to power decision-making for some of the world’s largest retailers.
About the role:
We're seeking an exceptional Head of Engineering to lead our technical organization through our next phase of growth. As our engineering leader, you'll build and scale our team, establish technical excellence, and drive the development of products that delight our customers. This is a unique opportunity to shape the engineering culture and technical foundation of an early-stage startup with ambitious goals.
What you’ll do:
- Lead engineering teams in designing and implementing scalable, cloud-native architectures for AI-powered, agent-based applications
- Drive technical strategy and establish engineering best practices across the organization with an AI-first approach
- Oversee the development lifecycle from planning through deployment using modern CI/CD pipelines
- Champion security-first development practices and ensure compliance with industry standards
- Mentor and develop engineering talent while fostering a culture of innovation and continuous improvement
- Build and maintain a hybrid engineering culture with effective collaboration practices across in-office and remote team members
- Collaborate with product, design, and business stakeholders to align technical solutions with retail customer needs
- Establish and monitor engineering KPIs, system performance metrics, and technical debt management
- Lead incident response protocols and ensure high availability of production systems
What we’re looking for:
- 10+ years of software development experience, including 5+ years in engineering leadership roles
- Strong application development background with hands-on experience scaling production systems
- Proven track record of scaling engineering teams from ~5 to 50+ engineers
- Ability to define who to hire and when, aligned to business and product priorities
- Experience building and maturing software development practices
- Deep expertise in modern programming languages, frameworks, and architectural patterns Strong understanding of distributed systems, microservices, and cloud infrastructure (AWS, GCP, or Azure)
- Experience building and scaling multi-tenant SaaS platforms
- Familiarity with modern data engineering, machine learning operations, or AI/ML infrastructure
- Experience with DevOps practices, containerization (Docker, Kubernetes), and infrastructure as code
- Experience with database design, optimization, and data architecture strategies
- Demonstrated ability to build and lead high-performing remote and distributed teams Excellent communication skills with ability to translate technical concepts for non-technical stakeholders
- Strong knowledge of Agile, Scrum, or other iterative development methodologies
Nice to have:
- Expertise in building platform engineering capabilities and developer experience initiatives Knowledge of observability tools and practices, particularly Honeycomb or similar event driven observability platforms
- Experience with security frameworks, penetration testing, and compliance requirements (SOC 2, GDPR, HIPAA)
- Early-stage startup experience with ability to thrive in ambiguous, fast-moving environments
- Experience in retail tech, e-commerce, or similar enterprise software platforms
- Bachelor's or Master's degree in Computer Science, Engineering, or equivalent practical experience
Apply today to join a small, senior team working on problems that sit at the core of how global retailers operate.
Profitmind is building the intelligence behind how retailers make pricing and merchandising decisions. Today, many of these decisions are still driven by spreadsheets, rigid rules, and manual judgment, even at the largest brands.
Our platform turns complex data such as sales, inventory, and competitive signals into clear, explainable recommendations merchants can trust. Our platform focuses on impact, helping retailers improve margin, inventory health, and decision quality at scale.
Based in Pittsburgh, Profitmind is backed by a recent strategic investment from Accenture, and scaling its agentic AI platform to power decision-making for some of the world’s largest retailers.
About the role:
We’re looking for a multi-disciplinary AI Engineer to design, implement, and deploy LLM-driven agents with strong backend and front-end integration. You’ll be leading efforts across LLM agent design, prompting, fine-tuning, and MLOps, while building real-world, production-grade applications with modern web technologies.
The ideal candidate combines a strong foundation in Python and AI with practical experience in agent frameworks like LangGraph, PydanticAI, and Google ADK, as well as FastAPI and front-end development.
What you’ll do:
LLM Agents & Prompt Engineering
- Architect and implement LLM agents using frameworks like LangGraph, PydanticAI, and Google ADK.
- Build composable, tool-augmented reasoning chains (e.g., RAG, CoT, ReAct, planner-executor).
- Integrate vector databases (e.g., FAISS, Pinecone, pgvector) and knowledge graphs (Neo4j) to support retrieval-augmented generation (RAG) and long-term chatbot memory.
- Design and maintain high-quality prompt strategies for robustness and reliability.
FastAPI, Model Context Protocol (MCP) & Backend
- Develop and maintain scalable APIs using FastAPI, supporting synchronous and asynchronous agent execution.
- Integrate Model Context Protocol (MCP) to enable secure and structured access to external data and tools within agent workflows.
- Implement state tracking, context-aware input dispatch, and modular plugin integration within the control plane.
Evaluation, Testing & Observability
- Build unit and behavioral tests for agents, tools, and workflows.
- Develop tooling for trace analysis, agent state debugging, and hallucination tracking.
- Compare and benchmark agent orchestration frameworks for trade-offs in speed, reliability, and usability.
Model Fine-Tuning & MLOps
- Fine-tune models using LoRA, QLoRA, or full fine-tuning pipelines.
- Integrate, deploy, and monitor models in production using cloud providers.
- Set up agent logging, observability dashboards, and recovery workflows.
Front-End & UX
- Familiar with React, TypeScript, Next.js, or similar frameworks
- Understanding of front-end and back-end integration for AI tools
- Ability to build basic dashboards or agent interfaces
- Integrate agents into interfaces
- Speak the language of UI
What we’re looking for:
- 3+ years experience with Python in ML/AI systems and PyTorch or Tensorflow
- 1+ years experience with LLM agent development, prompt engineering, and frameworks like
- LangGraph, PydanticAI, and Google ADK.
- Experience with fine-tuning LLMs.
- Familiarity using vector stores like ChromaDB, Weaviate, or pgvector.
- Production experience with FastAPI, Docker, and MLOps
- Expert in Agentic Coding IDEs (Windsurf, Cursor or Claude Code)
- Bachelor’s or Master's degree in computer science
Nice to have:
- Open-source contributions to LLM/agent tooling
- Knowledge of async programming, websockets, and streaming APIs
What we offer:
- Competitive compensation and equity
- Comprehensive benefits including medical, dental, vision, etc.
- Unlimited and flexible PTO
Profitmind is building the intelligence behind how retailers make pricing and merchandising decisions. Today, many of these decisions are still driven by spreadsheets, rigid rules, and manual judgment, even at the largest brands.
Our platform turns complex data such as sales, inventory, and competitive signals into clear, explainable recommendations merchants can trust. Our platform focuses on impact, helping retailers improve margin, inventory health, and decision quality at scale.
Based in Pittsburgh, we’re a fast-growing startup with real customers. Profitmind is backed by a recent strategic investment from Accenture, and is scaling its agentic AI platform to power decision-making for some of the world’s largest retailers.
About the role:
Profitmind is looking for a Full-Stack Software Engineer to help build and evolve the core product experience across both the frontend and backend. This role is frontend-heavy, but requires comfort working across the stack, including writing SQL queries and supporting backend data access in a JavaScript/TypeScript environment.
You’ll work closely with product, design, and engineering to turn complex data, workflows, and AI-driven functionality into experiences that feel simple, fast, and purposeful. This is a hands-on role for a mid-level engineer who can operate independently and work with the team to deliver features end-to-end.
What you’ll do:
- Build and maintain modern, responsive user interfaces across our web applications
- Develop and maintain reusable UI components within the core Profitmind product
- Work in a full-stack JavaScript/TypeScript environment, supporting both frontend features and backend data needs
- Write and maintain SQL queries to support product functionality and analytics use cases
- Support front-end and back-end integration for AI-powered tools and workflows
- Build dashboards and agent-style interfaces that make complex outputs easy to understand
- Write automated tests for frontend and full-stack functionality as part of a high-quality development process
- Ensure strong performance, accessibility, and cross-browser compatibility
- Iterate quickly based on user feedback and evolving product direction
What we’re looking for:
- 4–5 years of professional software development experience preferred
- Strong, hands-on experience building frontend applications using modern frameworks such as React, TypeScript, Next.js, or similar
- Comfort working across the stack in a JavaScript/TypeScript codebase
- Ability to write SQL queries independently and work with relational data on the backend
- Experience building data-driven user interfaces, dashboards, or analytics-heavy applications
- A pragmatic approach to automated testing and code quality
- High attention to detail and pride in delivering polished, usable software
- Ability to work independently in a fast-moving, product-driven environment
- Experience with enterprise, data-heavy, or analytics-focused products is a plus
What we offer:
- Competitive compensation and equity
- Comprehensive benefits including medical, dental, vision, etc.
- Unlimited and flexible PTO
This is a full-time position based in Pittsburgh, PA, though remote candidates will be considered on a case-by-case basis.
Apply today to join a small, senior team working on problems that sit at the core of how global retailers operate.
