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AI Engineer

Tekfortune

Job Location:

Chicago, IL - USA

Monthly Salary: Not provided by the employer

Posted: 8 September 2026 (11 hours ago)

Application Deadline: 6 December 2026

Vacancies: 1 Vacancy

Job Summary

Tekfortune is a fast-growing consulting firm specialized in permanent contract & project-based staffing services for worlds leading organizations in a broad range of this quickly changing economic landscape virtual recruiting and remote work are critical for the future of work. To support the active project demands and skills gaps our staffing experts can help you find the best job for you.

Job Position: AI Engineer
Location: Chicago IL USA Onsite

Mandatory Skills: Generative AI
Other skills: AWS Machine Learning Cloud & Data Engineering

Years Of Experience: 8 to 15 Years

Job Description
Role Summary & Objectives

Translate business automation and efficiency goals into scalable production-grade AI solution.
Design of autonomous multi-agent systems complex reasoning loops and tool-use workflows.
Establish robust guardrails human-in-the-loop decision controls and system observability.

Key Responsibilities
1. Agent Orchestration
Define multi-agent collaboration patterns memory management and autonomous planning frameworks.
2. Governance & Security
Implement data privacy compliance risk mitigation and evaluation guardrails across all AI touchpoints.
3. Cross-functional Leadership
Guide and mentor engineering teams run discovery workshops with stakeholders and define reusable deployment patterns.

Technical Stack & Expertise:
Generative AI & Agentic AI

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 Systems

Multi-agent coordination patterns (supervisor-worker decentralized collaboration stateful graphs).
Frameworks like LangChain LangGraph and Bedrock Core Runtime for state and memory management.
Emerging interoperability standards like Model Context Protocol (MCP) and Agent-to-Agent (A2A) protocols.

Data & Vector Technologies

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 & Infrastructure

Cloud-native deployment on AWS services including Amazon Bedrock Lambda EKS SageMaker S3 RDS and DocumentDB.
Containerization and orchestration using Docker and Kubernetes.
CI/CD pipelines for automated testing of non-deterministic AI outputs.

Observability & Responsible AI

Observability and logging pipelines for tracking agent token usage latency and failure states.
Responsible AI frameworks data privacy compliance and bias mitigation guardrails.

Roles & Responsibilities

Design and implement enterprise-scale Generative AI and Agentic AI solutions.
Develop and optimize RAG-based autonomous agent systems.
Drive AI governance security compliance and operational excellence.
Collaborate with business and technical stakeholders to deliver scalable AI solutions.
Mentor engineering teams and establish reusable deployment standards.

For more information and other jobs available please contact our recruitment team at . To view all the jobs available in the USA and Asia please visit our website at

Required Experience:

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