AI Engineer

**NO 3rd Parties or Sponsorship!

**MUST be able to provide a manager reference

Role Title: AI Engineer

Duration: 1 year contract, potential for hire

Preferred Location: Remote, must be able to support EST/CST hours

Role Description:
We''re looking for a Senior ML Engineer with strong hands-on experience in GenAI agent development and modern AI engineering. This role focuses on building production-grade agents, MCP integrations, and enterprise knowledge systems using our cloud and data stack.

• Design, build, and maintain production grade APIs, microservices, and internal SDKs that support AI models, LLM agents, retrieval pipelines, and tool integrations.
• Develop and refine GenAI and agentic systems, including MCP tools, secure system integrations, and scalable agent orchestration infrastructure.
• Create and maintain knowledge bases, retrieval pipelines, and vector search systems to power RAG and agent workflows across internal platforms.
• Implement comprehensive observability for LLM agents, retrieval pipelines, and AI microservices, covering monitoring, logging, tracing, drift detection, hallucination tracking, latency, cost, and quality metrics.
• Build automated evaluation and regression testing pipelines for agents, prompts, tools, and model updates to ensure reliability and continuous improvement.
• Develop frameworks for prompt versioning, experiment tracking, reproducibility, and model governance, ensuring consistent and auditable AI development practices.
• Establish and maintain MLOps and LLMOps pipelines, including model training, deployment, CI/CD and environment promotion (dev → QA → prod)
• Optimize model serving and inference infrastructure for performance and cost efficiency (batching, caching, quantization, GPU/CPU autoscaling).
• Collaborate with data scientists and cloud teams to productionize models, ensure reproducibility, and support scalable AI systems.
• Work across Azure, Snowflake, and Databricks to support production AI systems, data pipelines, and model deployments.

Requirements:

• 1+ years of experience building and deploying GenAI agents (including open-source LLM agents) in production environments
• Strong knowledge of MCP, tool integrations, and agent orchestration
• Ability to design and maintain knowledge bases, vector search, and retrieval systems
• Cloud expertise in Azure (preferred) or AWS
• Strong SQL skills and experience with Snowflake
• Experience working with Databricks for data and ML workflows
• Solid background in traditional ML (classification, clustering, etc.)
• Ability to build evals, guardrails, and safety layers for agents at scale
• Experience with MLOps and LLM Observability
• Experience building CI/CD pipelines (Github, DevOps)