Title: Forward Deployed AI Engineer
Location: Chicago, IL/Houston, TX
Minimum Exp.: 12+ years
Job Description
Key Responsibilities
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.