Title: AI Forward Deployed Engineer
Location: Chicago, IL / Houston, TX
Minimum Experience Needed: 12+ years
Job Description
- Architecture Design: Build enterprise Generative and Agentic AI platforms featuring high-performance RAG (Retrieval-Augmented Generation) pipelines and vector database integrations.
- Agent Orchestration: Define multi-agent collaboration patterns, memory management, and autonomous planning frameworks.
- Governance & Security: Implement data privacy, compliance, risk mitigation, and evaluation guardrails across all AI touchpoints.
- Cross-functional Leadership: Guide and mentor engineering teams, run discovery workshops with stakeholders, and define reusable deployment patterns.
Technical Stack
- Retrieval-Augmented Generation (RAG) pipelines, semantic caching, and context window optimization.
- Function calling, tool use, and structured data extraction schemas.
- Evaluation metrics, tracing, and hallucination reduction guardrails.
- Designing agentic first workflows and autonomous decision loops.
- Multi-agent coordination patterns (supervisor-worker, decentralized collaboration, stateful graphs).
- Frameworks like LangChain/LangGraph/Bedrock Core Runtime for state and memory management.
- Emerging interoperability standards like Model Context Protocol (MCP) and Agent-to-Agent (A2A) protocols.
- Vector databases (e.g., Milvus, Amazon Aurora PostgreSQL) for high-speed similarity search.
- Data pipelines and embedding generation workflows using Python, FastAPI, or Apache Spark.
- Cloud-native deployment on platforms like AWS (Amazon Bedrock, Lambda, EKS, SageMaker, S3, RDS, DocumentDB)
- Containerization and orchestration tools including Docker and Kubernetes.
- CI/CD pipelines for automated testing of non-deterministic AI outputs.
- Observability and logging pipelines for tracking agent token usage, latency, and failure states.
- Responsible AI frameworks, data privacy compliance, and bias mitigation guardrails.