Software Engineer – Agentic AI Specialist

Techunting; Chicago (IL); On-site; USD 130,000 - 210,000; Full time

Job summary

Techunting onsite in Chicago is seeking a Forward Deployed Engineer to design, prototype, and deploy AI and data-driven solutions. You will work directly with experts across product and engineering to move from concept to working prototype in days, not months.

The role requires hands-on experience with AI agents and full-stack development, and the ability to communicate architecture clearly to stakeholders. You will operate at enterprise scale with security and reliability in mind.

Qualifications

• Hands-on engineering experience across AI agents and full-stack development.
• Ability to design and communicate architecture to non-technical stakeholders.
• Experience prototyping quickly from concept to working solution.

Responsibilities

• Lead solution design for complex data and AI problems from discovery to blueprint.
• Translate requirements into scalable, secure architectures.
• Prototype rapidly, delivering production-ready solutions.
• Collaborate with product, program, and engineering teams and mentor junior engineers.

Skills

AI agents

Full-stack development

Architecture design

Documentation

Communication

Mentoring

UX

Frontend development

Tools

AWS Agent Core

APIs

Job description

Location: Onsite (Chicago, IL) preferred

Role Overview

As a Forward Deployed Engineer, you will operate at the front lines of innovation — embedded directly with subject matter experts, product, and engineering teams to rapidly design, architect, prototype, and deploy solutions that solve high-priority business problems. This is not a traditional engineering role with long delivery cycles. You will be expected to go from concept to working prototype in days, not months, while maintaining enterprise-grade standards for quality, security, and scalability.

You bring an exceptional combination of skills: deep hands-on engineering experience across AI agents and full-stack development, and the interpersonal skills to earn trust, drive alignment, and influence without authority. You are equally comfortable whiteboarding a system architecture with senior stakeholders and writing production code the same afternoon. You have direct experience developing agents on platforms like AWS Agent Core, and you thrive in fast, ambiguous environments where creative thinking and execution speed matter.

Key Responsibilities

Solution Design & Architecture

• Lead solution design for complex, cross-functional data and AI problems — from initial discovery through to technical blueprint
• Define and communicate architecture decisions, trade-offs, and delivery approaches to both technical and non-technical audiences
• Design scalable, modular systems that balance the need for speed with enterprise standards for reliability, security, and maintainability
• Participate in architecture reviews, ensuring alignment with enterprise patterns and platform standards
• Create clear technical documentation: architecture diagrams, data flow maps, API contracts, and solution briefs

Rapid Prototyping & Solution Delivery

• Design and deliver working prototypes for complex data and AI problems within compressed timeframes, often days to weeks
• Translate ambiguous business requirements into concrete technical solutions with minimal hand-holding
• Balance speed of delivery with enterprise standards — your prototypes are production-ready, not throwaway
• Continuously iterate on solutions based on direct feedback from product managers, program leads, and end users
• Develop intuitive front-end interfaces and dashboards that bring data and AI outputs to life for business users
• Apply strong UX instincts to simplify complex flows and make agent outputs accessible and actionable for non-technical stakeholders

AI Agent Development

• Design, build, and deploy AI agents and multi-agent systems that automate complex workflows end-to-end
• Develop and maintain agent skills — discrete, reusable capabilities that compose into larger agentic pipelines
• Implement and extend Model Context Protocol (MCP) servers and clients to connect AI agents with enterprise tools, APIs, and data sources
• Design evaluation harnesses, guardrails, and monitoring pipelines to ensure agent reliability and safety in production
• Stay current with the rapidly evolving agentic AI landscape and proactively introduce new techniques and tooling to the team
• Integrate LLMs, RAG systems, and ML models into production workflows

Collaboration & Stakeholder Engagement

• Embed directly with product, program, and engineering teams to co-define problems and co-deliver solutions
• Influence technical direction and build alignment across teams without relying on formal authority
• Communicate complex technical concepts clearly to non-technical business stakeholders — in writing, in meetings, and in executive presentations
• Mentor and elevate junior engineers, sharing patterns and practices for agentic development, prompt design, and rapid delivery
• Foster a collaborative, low-ego team culture where speed and quality go hand in hand