Note: The job is a remote job and is open to candidates in USA. CDW is a leading multi-brand provider of information technology solutions to various sectors in the United States. They are seeking a Senior AI Engineer to transition AI capabilities from prototype to production, architecting robust systems that can autonomously handle complex workflows and collaborating with teams to deliver effective AI agents.
Responsibilities
- Agentic Engineering & Orchestration
- Workflow Design: Architect complex, multi-agent workflows using Microsoft AI tech stack. Design, Develop and Deploy agents to handle loops, interruptions, and human-in-the-loop interventions
- Tool Use & Function Calling: Build reliable "tool layers" that allow LLMs to safely interact with internal APIs, databases, and third-party SaaS platforms (e.g., SalesForce, Workday, ServiceNow etc.)
- State Management: Design persistence layers to manage agent memory, conversational history, and context windows efficiently
- Advanced Data & RAG Strategy
- Retrieval Pipelines: Build production-grade data retrieval and integration systems. Optimize vector indexing, document chunking, and re-ranking algorithms to ensure high-precision context retrieval
- Data Quality: Collaborate with Data Engineers to curate "Golden Datasets" for agent consumption
- LLMOps, Evaluation & Quality
- Automated Evaluation: Build CI/CD pipelines for AI that include "LLM-as-a-Judge" testing. Leverage frameworks to score agent outputs for accuracy, hallucination, and safety before deployment
- Observability: Instrument applications with tracing tools to visualize agent reasoning chains, monitor latency, and debug failures in production
- Cost Optimization: Monitor token usage and latency, optimizing prompt density and caching strategies to maintain high performance at sustainable costs
- Innovation & Collaboration
- Prototyping to Production: Rapidly validate new ideas using state-of-the-art models, then refactor successful prototypes into maintainable, tested production code
- Standards Adoption: Stay ahead of the curve by evaluating emerging technologies to standardize agent connectivity
Skills
- Bachelor's degree and 5 years of software engineering experience, with exposure to AI/ML applications OR 9 years of software engineering experience, with exposure to AI/ML applications
- 2+ years specifically building with LLMs, with deep familiarity in: Orchestration: LangChain, LangGraph, or similar state-based frameworks
- Vector DBs: Pinecone, Weaviate, or pgvector
- Prompt Engineering: Advanced techniques (Chain-of-Thought, ReAct, Few-Shot)
- Experience not just building demos, but operating them. You know how to handle rate limits, context window overflows, and non-deterministic errors
- Ability to explain 'probabilistic software' to non-technical stakeholders—managing expectations that agents are never 100% accurate, but can be 100% useful
- Excellent communication skills, with experience in documenting technical designs, sharing insights, and enabling team knowledge transfer
Benefits
- Benefits overview: https://cdw.benefit-info.com/
- Salary ranges may be subject to geographic differentials
Company Overview
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