• Build and productionize multi-agent workflows on Anthropic/OpenAI APIs: orchestration, tool use, structured outputs, guardrails. • Design hybrid retrieval architectures that combine knowledge graphs, vector search, and ranking into a single coherent context layer. • Build evaluation harnesses and observability for agent behavior — quality, latency, cost — and use them to drive iteration. • Integrate LLM inference, retrieval, and reasoning services into production backends. • Work with researchers and domain experts to turn neuro-symbolic prototypes into robust product features.

Role Description CODEplus is currently seeking an AI/ML Engineer to support its operations in Atlanta, GA or Washington D.C., or Remote. Preference will be given to candidates located in Atlanta, GA or the D.C. Metro area. True innovation happens where machine learning meets cloud technology and real-world impact. As an AI/ML Engineer, you’ll join a collaborative team of technologists, data scientists, and stakeholders to tackle meaningful challenges using ML, Generative AI, and modern tools. You’ll contribute to building and scaling intelligent systems—from core ML models to chatbot and Retrieval-Augmented Generation (RAG) applications. With strong skills in Python, SQL, and cloud platforms like Azure, you’ll help deliver practical, forward-looking solutions in dynamic environments. Bring your technical expertise, curiosity, and customer-first mindset to help shape the future of intelligent systems across industries. Core Responsibilities: - Design, develop, and deploy scalable machine learning models and AI-driven solutions to address complex business and operational challenges. - Build and enhance Generative AI, LLM, and Retrieval-Augmented Generation (RAG) applications, including chatbot and conversational AI capabilities. - Develop and optimize data pipelines, feature engineering workflows, and large-scale data processing solutions using Python, SQL, and Spark. - Implement and support MLOps practices, including model training, deployment, monitoring, and lifecycle management using tools such as MLflow and Azure cloud services. - Collaborate with cross-functional teams and stakeholders to deliver customer-focused AI/ML solutions while staying current on emerging technologies and industry best practices. Qualifications - 3+ years of experience designing, developing, and deploying machine learning models. - 3+ years of experience with Generative AI, LLMs, or RAG applications. - 4+ years of hands-on experience with Python for ML and data engineering. - Experience with SQL for data manipulation and feature engineering. - Experience with big data tools such as Apache Spark. - Experience with Databricks and MLOps tools like MLflow. - Experience with cloud, preferably in Azure. - Ability to exhibit strong communication and customer-facing skills. - Ability to thrive both independently and in cross-functional teams. - Ability to problem solve and stay current with emerging ML trends. Nice If You Have - Experience with full-stack development or deploying end-to-end ML applications. - Experience with chatbot development or conversational AI. - Experience fine-tuning large models. - Experience with deploying ML solutions using MLOps pipelines. - Knowledge of Agile workflows and tools like JIRA.

• Build and deliver AI solutions: Take ownership of developing delightful, high-performance AI features to help users discover, organize, and optimize access to large datasets. • Rapid experimentation and iteration: Implement a highly iterative process where you quickly prototype, test, and validate with real users, including shipping and evolving LLM- or agent-powered workflows for the data engineering lifecycle. • Collaborate: Work with the rest of the team to shape AI-driven product features, including the integration of agentic components with internal tools like Slack and alerting systems while engaging with internal data teams for dogfooding. • Utilize AI tools effectively: Use AI and automation tools to enhance both product functionality and your own development workflows. • Effective communication: You’ll be working in a highly dynamic and collaborative environment, so we need someone who can communicate effectively and contribute across teams. • Ownership and impact: Take full ownership of the AI solutions you develop, ensuring they are not only innovative but also scalable, maintainable, and aligned with real user workflows.

• Architect and scale our GTM systems across sales, marketing, and product • Lead development of AI agents and workflows that automate key parts of the funnel • Orchestrate tools like Salesforce and HubSpot into a unified system • Turn product and user data into actionable growth signals • Build intelligent workflows (lead scoring, routing, outbound triggers, onboarding flows) • Define how AI is used across the entire customer lifecycle • Identify bottlenecks and design systems to remove them • Partner closely with founders on growth strategy, experiments, and priorities