Forward Deployed AI Engineer

Tekfortune is a fast-growing consulting firm specialized in permanent, contract & project-based staffing services for world's leading organizations in a broad range of industries. In 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: Forward Deployed AI Engineer
Location: Chicago, IL or Houston, TX


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.

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