Senior AI Engineer at STAFFWORXS in Summit, NJ

Job description

• We are looking for a Senior AI Engineer to design, build, and run production AI solutions, including AI agents, retrieval-augmented generation (RAG), and LLM-powered automation. You will take use cases from discovery to production, making sure solutions are reliable, secure, and cost-effective.

Responsibilities

• Design and build AI agents and multi-step agentic workflows that automate business processes.
• Integrate LLMs with internal systems and data through APIs and MCP (Model Context Protocol).
• Build RAG, vector search, and embedding pipelines over documents and knowledge bases.
• Develop document processing pipelines to extract and validate structured data.
• Implement output validation, evaluation frameworks, and human-in-the-loop review.
• Build AI observability covering quality, latency, failure rates, and cost, with alerting.
• Work with data engineering teams on AI-ready data pipelines and models.
• Enforce data security, privacy, and PII handling across AI solutions.
• Own CI/CD, infrastructure-as-code, and deployment of AI services.
• Work with business stakeholders to scope use cases and define success metrics.
• Write architecture decision records, review code, and mentor engineers.

Requirements

• 8+ years in software, data, or ML engineering, including 2+ years delivering LLM or GenAI solutions to production.
• Strong Python and SQL skills.
• Hands-on experience with LLM APIs (OpenAI, Anthropic, Azure OpenAI), prompt engineering, and structured outputs.
• Proven experience with RAG, vector databases, and embeddings.
• Experience building AI agents or agentic workflows.
• Solid data engineering background with a cloud data platform (Snowflake, Databricks, or similar), orchestration (Airflow or similar), and dbt.
• Production experience on AWS, Azure, or GCP, with Docker, CI/CD, and Terraform.
• Understanding of data security, privacy, and governance.
• Strong communication skills with both technical and non-technical audiences.
• Experience building MCP servers or gateways.
• Intelligent document processing or OCR experience.
• MLOps experience, including feature stores, model deployment, and GPU inference.
• Experience with AI evaluation, observability, and cost optimization.
• Background in financial services or another regulated industry.
• Master's degree in Computer Science, AI, or a related field.
• Cloud or data platform certifications (AWS ML, Snowflake, Azure AI).
• Regular use of AI-assisted development tools such as Claude Code or GitHub Copilot.

Skills

Required

• Python
• SQL
• Prompt engineering
• Structured outputs
• RAG
• Vector databases
• Embeddings
• AI agents
• Agentic workflows
• Orchestration (Airflow or similar)
• dbt
• AWS, Azure, or GCP

Preferred

• MCP servers or gateways
• Intelligent document processing
• OCR
• MLOps
• Feature stores
• Model deployment
• GPU inference
• AI evaluation