AI Engineer (Contract)

RBA is a trusted consulting partner helping enterprise and mid-sized organizations transform their businesses through modern technology solutions. We blend strategic thinking with deep technical expertise to deliver scalable, high-impact outcomes aligned to our clients’ goals. Our team partners with some of the most recognized companies in our market while fostering a culture that values collaboration, innovation, and continuous learning.

We are seeking an AI Engineer to join our growing team. This is a client-facing, consultative role for someone who enjoys building production-ready AI solutions while partnering with clients to solve complex business challenges.

In this role, you’ll design and deliver modern AI applications that leverage machine learning, large language models, and cloud-native technologies. You’ll work across the full solution lifecycle. This means involvement from architecture and engineering through deployment and optimization; with your help, organizations will responsibly adopt AI at scale.

What You’ll Do

• Design, develop, and deploy end-to-end AI applications using modern software engineering and machine learning practices
• Build scalable APIs and user interfaces that make AI-powered capabilities accessible to business users
• Develop and optimize machine learning models for predictive analytics, personalization, automation, and intelligent decision support
• Design and implement Retrieval-Augmented Generation (RAG) architectures and LLM-powered applications
• Build agentic AI workflows capable of multi-step reasoning, orchestration, and tool integration
• Implement AI governance, safety guardrails, and observability to ensure secure, reliable, and responsible AI solutions
• Monitor production AI systems for performance, latency, model quality, hallucination rates, and overall application health
• Design cloud-native AI solutions utilizing containers, Kubernetes, CI/CD pipelines, and modern DevOps practices
• Collaborate with client stakeholders to understand business objectives and translate requirements into scalable AI solutions
• Partner with data engineers, software engineers, architects, and strategists throughout client engagements
• Contribute to technical solution design during client pursuits and support AI-related innovation across the practice
• Mentor junior engineers and contribute to internal AI best practices, reusable accelerators, and thought leadership

What You Bring

• 5+ years of experience in software engineering, AI engineering, or machine learning engineering
• Strong proficiency with Python and experience building modern backend services using Node.js, NestJS, or similar frameworks
• Experience developing modern front-end applications using React or comparable frameworks
• Hands-on experience deploying machine learning models into production environments
• Experience building applications utilizing Large Language Models (OpenAI, Claude, Gemini, or similar)
• Practical experience implementing Retrieval-Augmented Generation (RAG), prompt engineering, semantic search, and vector databases
• Strong understanding of AI application architecture, orchestration frameworks, and agentic workflows
• Experience designing REST APIs and integrating AI capabilities into enterprise applications
• Experience with SQL and modern data engineering concepts, including ETL/ELT and data governance
• Experience deploying cloud-native applications in Azure, AWS, or GCP
• Familiarity with Docker, Kubernetes, Terraform, CI/CD pipelines, and Infrastructure as Code
• Strong communication skills with the ability to explain technical concepts to both technical and business audiences
• Experience working directly with clients, gathering requirements, and delivering consulting engagements

Nice to Have

• Experience with frameworks such as LangChain, LangGraph, LlamaIndex, CrewAI, Semantic Kernel, or similar orchestration platforms
• Experience with PyTorch, TensorFlow, Scikit-learn, or other ML frameworks
• Experience with Databricks, Microsoft Fabric, Snowflake, or modern AI-enabled data platforms
• Experience implementing AI governance, responsible AI, and model monitoring practices
• Experience with vector databases such as Pinecone, Azure AI Search, Weaviate, Milvus, or pgvector
• Experience deploying multimodal AI solutions
• Azure, AWS, Google Cloud, Databricks, or AI-related certifications
• Experience supporting MLOps platforms and automated model deployment

Why RBA?

At RBA, you’ll work alongside experienced consultants solving meaningful problems across a variety of industries. Every engagement presents new opportunities to apply emerging AI technologies, collaborate with talented teams, and help clients realize measurable business value. We invest in our people through continuous learning, innovation, and a culture that encourages curiosity, collaboration, and professional growth.