Senior Associate – AI ML Engineer

The role

You will build and maintain end-to-end AI/ML and Generative AI applications. This includes designing RAG solutions, developing agentic workflows, and integrating foundation models. You will also create evaluation pipelines and develop production services using Python.

What you will do

• Build and maintain end-to-end AI/ML and Generative AI applications.
• Design Retrieval-Augmented Generation (RAG) solutions.
• Develop agentic AI workflows.
• Integrate foundation models and AI services from commercial and open-source ecosystems.
• Implement prompt engineering, few-shot patterns, and fine-tuning.
• Create reproducible evaluation pipelines for accuracy, relevance, and safety.
• Develop production services using Python and REST APIs.
• Use Git and GitHub for version control and CI/CD workflows.
• Containerize and deploy applications using Docker and cloud services.
• Apply secure AI development practices.

Required qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Engineering, or a related field—or equivalent practical experience.
• 3–5 years of professional experience developing software, data, or machine learning solutions, including substantial hands-on experience with Generative AI or LLM-based applications.
• Strong Python programming skills and practical experience with common data and ML libraries such as pandas, NumPy, scikit-learn, PyTorch, TensorFlow, or equivalent.
• Working knowledge of LLM application patterns such as prompting, embeddings, RAG, vector databases, tool/function calling, structured outputs, and agent workflows.
• Experience building and consuming REST APIs, working with JSON and schemas, and integrating databases, enterprise systems, or external services.
• Understanding of software-engineering practices: object-oriented or modular design, unit and integration testing, logging, error handling, code review, documentation, and debugging.
• Hands-on experience with Git/GitHub and CI/CD concepts.
• Experience with at least one cloud platform (AWS, Azure, or GCP) and containerization using Docker.
• A current, role-relevant AWS AI/ML certification or Microsoft Azure AI certification is mandatory.
• Understanding of ML/LLM evaluation, experiment tracking, model or prompt versioning, observability, and production monitoring.
• Strong analytical, communication, and collaboration skills.

Nice to have

• Experience with one or more GenAI/agent frameworks or SDKs, such as OpenAI Agents SDK, LangGraph/LangChain, Semantic Kernel, LlamaIndex, AutoGen, or similar.
• Experience with vector stores or search platforms such as pgvector, Pinecone, Weaviate, Milvus, Elasticsearch/OpenSearch, Azure AI Search, or equivalent.
• Exposure to LLMOps/MLOps tooling for experiment tracking, tracing, evaluation, model registry, prompt management, or monitoring.
• Knowledge of SQL and data modeling.
• Exposure to streaming, queues, workflow orchestration, or distributed processing is a plus.
• Experience applying AI to enterprise use cases such as finance, accounting, operations, customer service, document intelligence, software engineering, analytics, or workflow automation.
• Awareness of responsible AI, bias and risk assessment, data governance, secure development, and regulatory or client-compliance requirements.
• Open-source contributions, technical writing, hackathon projects, or a portfolio demonstrating deployed AI applications.

Benefits

• Medical insurance
• Dental insurance
• Vision insurance
• 401(k) with company match
• PTO

About the company

Riveron partners with clients to solve complex finance challenges, guided by their DELTA values. Their entrepreneurial culture thrives on collaboration and delivering exceptional outcomes.