Forward Deployed Engineer
$31,200–$31,200 year
On-siteChicago, Illinois, United States or San Francisco, California, United States
Job Summary
Design scalable, modular systems and deliver production-ready prototypes for complex data and AI problems within compressed timeframes. Lead solution architecture for cross-functional challenges, defining trade-offs and communicating technical blueprints to both technical and non-technical stakeholders. Build and deploy AI agents and multi-agent systems that automate workflows, integrating LLMs, RAG, and ML models into enterprise production environments. Establish evaluation harnesses, guardrails, and monitoring pipelines to ensure agent reliability and safety while maintaining enterprise-grade standards for security and scalability. Collaborate directly with product and engineering teams to co-define problems, influence technical direction without formal authority, and mentor junior engineers in rapid delivery practices.
Required Qualifications
- 8+ years of professional software engineering experience, including solution design and architecture ownership
- Demonstrated ability to architect end-to-end systems — from requirements through deployment — with clear documentation and stakeholder communication
- Hands-on experience building AI agents, including defining agent skills, tool use, memory, and multi-step reasoning
- Experience with AI-Augmented Engineering (Harness Engineering) — actively use tools like Claude Code, Codex, or equivalent assistants to accelerate coding, documentation, and problem-solving day-to-day
- Direct experience with AWS Agent Core or equivalent — building, deploying, and operating agents in production
- Working knowledge of Model Context Protocol (MCP) — including building or consuming MCP servers to connect agents with external systems
- Experience with agentic frameworks such as LangChain, LangGraph, AutoGen, CrewAI, or Semantic Kernel
- Proficiency in Python and at least one front-end framework (React, Vue.js, or Angular)
- Experience with cloud platforms (AWS, Azure, or GCP)
- Exceptional communication and interpersonal skills — you can earn trust quickly, navigate ambiguity, and drive alignment across diverse teams
- Comfort working in fast-paced environments with shifting priorities and high ownership expectations
- Candidates must be authorized to work in the United States without sponsorship
Desired Qualifications
- Experience with RAG architectures, vector databases (Pinecone, Weaviate, pgvector), and semantic search
- Familiarity with prompt engineering, fine-tuning, and LLM evaluation techniques
- Experience with agent observability and tracing tools (LangSmith, Arize, Weights & Biases, or similar)
- Experience with containerization and CI/CD practices (Docker, Kubernetes, GitHub Actions)
- Background in real estate, financial services, or other data-intensive enterprise domains
- Experience facilitating technical discovery workshops, design sprints, or architecture reviews
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