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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Software Engineer - **Company:** Robert Half - **Location:** Atlanta, GA, United States - **Experience:** Experienced - **Contract:** Temporary contract - **Skills:** Artificial Intelligence, Amazon Web Services, Software Applications, Microsoft Azure, Big Data, Information Leak Prevention, Data Visualization, Django Web Framework, Python (Programming Language), Machine Learning, Node.Js, Power BI, Tensorflow, Software Engineering, Systems Integration, TypeScript, Unstructured Data, Google Cloud, Enterprise Software Applications, Cloud Platform System, Pytorch, ReactJS, Flask (Web Framework), Large Language Models, Snowflake, Multi-Agent Systems, Prompt Engineering, Model Validation, Fastapi, Build Management, AI Platforms, Kubernetes, Data Management, Machine Learning Operations, Tools for Reporting, Api Design, Restful APIs, Azure Synapse Analytics, GPT, Docker, Amazon Redshift, Databricks, Microservices - **Published:** May 17, 2026 - **Apply:** https://www.juju.com/job/00000000g04i4m ## About the Role + 3-5+ years of experience in AI/ML Engineering, Data Science, or Software Engineering Strong Python skills with ML frameworks (TensorFlow, PyTorch, etc.) + Experience building LLM-based solutions (OpenAI, Anthropic/Claudecode, Gemini, Copilot, etc.) Hands-on experience with AI orchestration frameworks (LangChain, LlamaIndex, Semantic Kernel, etc.) + Strong experience with API development and system design Experience working with large datasets and integrating across enterprise systems Proficiency in data visualization/reporting tools (Power BI or similar) + Experience designing and deploying production-grade AI systems in cloud environments Strong understanding of model evaluation, data quality, and AI system performance + Proven ability to partner cross-functionally and manage multiple stakeholders + Strong communication skills and ability to operate in consulting/client-facing environments Self-starter with the ability to adapt quickly across business domains Requirements Nice to Have + Experience with vector databases (Pinecone, FAISS) + Exposure to RAG architectures, prompt engineering, and agentic AI systems MLOps tools (MLflow, Kubeflow, Docker, Kubernetes) + Experience with data platforms (Snowflake, Databricks, Redshift, Synapse) + Full-stack experience (React, TypeScript, Node.js) + Experience evaluating and integrating 3rd party AI tools Prior consulting or contract delivery experience, All applicants applying for U.S. job openings must be legally authorized to work in the United States. Benefits are available to contract/temporary professionals, including medical, vision, dental, and life and disability insurance. Hired contract/temporary professionals are also eligible to enroll in our company 401(k) plan. Visit roberthalf.gobenefits.net for more information. ## Description + We're seeking experienced AI/ML Engineers interested in consulting-driven work to design, build, and deploy enterprise-grade AI solutions. This role focuses on delivering scalable ML and GenAI systems that drive automation, insights, and operational efficiency across multiple business functions. You'll operate as an internal consultant and technical leader, partnering with stakeholders to identify opportunities, implement AI tools, and bring solutions from concept to production. What You'll Do + Design and own end-to-end AI/ML and GenAI solutions, including LLM-based applications and predictive models Collaborate across multiple business units to identify, scope, and deliver high-impact AI use cases Build and deploy AI-powered applications (RAG pipelines, agentic workflows, automation tools) + Evaluate, recommend, and integrate third-party AI platforms and vendors Develop scalable APIs, pipelines, and microservices using Python (FastAPI, Flask, Django) and cloud platforms (AWS, Azure, GCP) + Leverage tools like ChatGPT, Claude, Gemini, and Copilot to automate workflows and generate insights from structured and unstructured data + Create dashboards and reporting solutions using Power BI or similar tools to drive data-informed decisions Translate business requirements into technical architectures and production-ready systems Implement evaluation frameworks, metrics, and monitoring for model performance and business impact + Ensure secure, scalable, and compliant deployment of AI solutions Identify risks (bias, hallucination, data leakage) and implement mitigation strategies Act as a trusted AI advisor, proactively identifying opportunities to drive efficiency and innovation ## Related Videos - [ Evaluating AI models for code comprehension](https://www.wearedevelopers.com/videos/1462-evaluating-ai-models-for-code-comprehension) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. 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