10271

3Core Systems; Chicago (IL); Hybrid; USD 165,000 - 262,000; Full time

Job summary

3Core Systems, Inc. is seeking a Lead AI Software Engineer in Chicago (Hybrid – 2 days onsite) to architect and deliver state-of-the-art AI-driven software. You will guide multiple teams, design multi-agent workflows, and integrate large language models via secure APIs, balancing performance, cost, and security.

The role emphasizes cloud-native architecture, API design, and scalable AI platforms with governance and mentoring responsibilities. A Bachelor’s degree is required.

Qualifications

• 8+ years in professional software engineering with leadership exposure.
• Experience designing large-scale distributed systems and APIs.
• Strong architecture, cloud-native practices and governance.
• Proven ability to mentor teams and drive technical initiatives.
• Hands-on with Generative AI, AI agents, LLM-powered apps.

Responsibilities

• Design multi-agent workflows and stateful AI systems using modern frameworks.
• Integrate foundation models via secure API gateways with cost controls.
• Architect data models combining relational and vector stores for RAG.
• Lead security, testing, and continuous improvement across teams.
• Coach developers on responsible AI use and governance.

Skills

AI

API

Java

LLMs

Microservices

RAG

AWS

Technical Leadership

Education

Bachelor's Degree

Tools

LangChain

LangGraph

AutoGen

CrewAI

Docker

Kubernetes

Windsurf

Cursor

Claude Code

Job description

Chicago, United States | Posted on 10/30/2026

Role: Lead AI Software Engineer ( 507554 )

Location: Chicago,IL (Hybrid – 2 Days a week onsite)

Duration: 12 MonthContract

Must HaveSkills/Attributes : AI, API, AWS, Java, LLM (LargeLanguage Model), Microservices, RAG (Retrieval-Augmented Generation)

Experience Desired

• JavaBackend Development
• Microservices& API Architecture (10+ Years)
• SoftwareArchitecture & Large-Scale Distributed Systems (8+ Years)
• GenerativeAI, LLMs, AI Agents, Prompt Engineering & RAG(LangChain/LangGraph/AutoGen/CrewAI) (3+ Years)
• TechnicalLeadership, Engineering Governance & Mentoring Multiple Teams (2+ Years)

Required MinimumEducation : Bachelor’s Degree

Job Description

RequiredEducation/Experience

• Bachelor’s degree in Computer science orElectrical engineering or related field

Required TechnicalSkills

• 8+ years of professional software engineeringexperience and 2+ years in a technical leadership role.
• Proven experience designing and deliveringlarge-scale distributed systems.
• Strong expertise in software architecture,APIs, microservices, cloud-native applications, and modern engineeringpractices.
• Experience influencing multiple engineeringteams and leading organization-wide technical initiatives.
• Strong communication, collaboration, andstakeholder management skills.
• Demonstrated ability to mentor engineers anddrive technical excellence.
• Experience with Generative AI, AI agents,LLM-powered applications, or intelligent automation platforms.
• Experience with AI development tools, codingassistants, and modern developer productivity platforms.
• Knowledge of security architecture,application security, and cloud security best practices.
• Experience establishing technical governanceand engineering standards across multiple teams.

Required Soft Skills

• Ability to work under pressure and withintime constraints
• Passion for technology and an eagerness tocontribute to a team-oriented environment
• Lead architectural designs and able to workacross teams to come up with solutions.

Summary of Role

• Design and orchestrate multi-agent workflowsand stateful AI systems using modern frameworks like LangChain, LangGraph,AutoGen, or CrewAI.
• Integrate foundation models (e.g., AnthropicClaude, OpenAI GPT, Google Gemini) via secure API gateways, managing tokenlimits, costs, and rate-limiting.
• Architect data models optimized for AI-nativestructures, integrating relational databases with vector databases for semanticsearch and Retrieval-Augmented Generation (RAG).
• Implement robust white-box testing andcontinuous evaluation metrics to monitor AI outputs for factual correctness,hallucinations, and safety compliance.
• Champion secure, reliable, and scalablesoftware solutions through architectural leadership, risk management, andcontinuous improvement of engineering practices.

Technical Leadership& Workflow Optimization

• Mentor and scale an engineering team,establishing engineering standards, best practices and architectural governancefor secure coding, continuous integration, and cloud-native deployment.
• Drive AI-assisted engineering velocity byintegrating next-gen development tools (e.g., Cursor, Claude Code, Windsurf)into the team's daily Software Development Life Cycle (SDLC).
• Establish governance policies and coachdevelopers on the responsible use of AI, focusing on input data sensitivity,license compliance, and security guardrails.
• Evaluate existing systems, services, APIs,and data models to identify opportunities for modernization, scalability, andperformance improvements.

Influence Across Teams& Champion Developer Experience

• Facilitate technical leadership forums withProduct Owners, Technical Leads, Architects, and Engineering Managers.
• Drive conversations around architecture,engineering health, technical debt, AI adoption, and continuous improvement.
• Mentor engineers and technical leaders onsystem design, software architecture, and engineering excellence.
• Foster collaborative decision-making througharchitecture reviews, RFCs, and technical discussions.
• Promote self-service engineering capabilitiesand platform enablement.
• Drive automation initiatives that improveproductivity and software quality.

Interaction with team

• Significant interaction required with Scrumteam. Interaction during all scrum ceremonies such as Daily Standups, SprintPlanning, Grooming, Retro, Demo etc
• Also need to interact with team for PRReviews, also need to engage with other teams as needed.

Core SoftwareEngineering

• Backend Systems: Deep proficiency in backendenvironments, microservices architectures, and API design using Java.
• Cloud & DevOps: Extensive experience withcontainerization (Docker, Kubernetes) and public cloud infrastructure like AWSAI & LLM Infrastructure
• Orchestration & Tooling: Hands-on experiencewith production-level AI agents, prompt engineering, and advanced Agentic PDLCpatterns.
• Vector Databases: Practical knowledge ofvector technologies such as Pinecone, Milvus, Chroma, or pgvector.
• AI Tool Fluency: Demonstrated mastery of AIcoding assistants and a firm understanding of Model Context Protocol (MCP) tomediate agent connections with external databases.