Gen AI - Data Engineer with AWS Experience

Dallas, TX, United States (On-site)

Contract (9 months 5 days)

Published 5 hours ago

Lakehouse Architecture

Security & Governance

Production Deployment

Vector databases

performance optimization

AI Testing & Validation

Observability & Monitoring

Seeking a Store AI Agent Lead to architect, build, and scale AI-powered agents supporting store operations. The role requires strong hands-on experience with Agentic AI, LLMs, RAG, vector search, AWS, and enterprise system integration, along with the ability to take solutions from architecture through production.

Key Responsibilities:

• Lead the end-to-end architecture and implementation of Store AI Agents.
• Design agentic workflows integrating LLMs with APIs, databases, backend services, enterprise applications, and MCP servers.
• Build and optimize RAG solutions, including embeddings, retrieval, vector search, grounding, and context management.
• Define the process for onboarding and integrating new AI agents, including testing, deployment, monitoring, and production readiness.
• Establish clear architecture between LLM reasoning/generation and deterministic backend services.
• Leverage Lakehouse/Medallion architecture (Bronze, Silver, Gold) to support AI and data use cases.
• Define scalable approaches for AI/RAG testing, validation, observability, and performance optimization.
• Address production challenges including latency, context limitations, retrieval quality, scalability, and reliability.
• Provide technical leadership across AI/ML, data engineering, cloud, application, and business teams.

Required Skills & Experience:

• Proven experience delivering at least one end-to-end LLM, RAG, or Agentic AI project.
• Strong architectural and hands-on experience with Generative AI on AWS.
• Hands-on knowledge of LLMs, RAG, embeddings, vector search, and agentic workflows.
• Experience integrating AI agents with APIs, databases, backend services, and enterprise systems.
• Understanding of MCP (Model Context Protocol) and agent-to-tool/service integration.
• Experience with Lakehouse and Medallion Architecture and data pipeline optimization.
• Strong understanding of AI testing, observability, security, scalability, latency, and production performance.
• Ability to articulate end-to-end architecture, technology choices, integration patterns, and design trade-offs.

Preferred:

• Experience with AWS-based GenAI and data platforms.
• Experience building enterprise-scale AI agents or multi-agent solutions.
• Exposure to modern vector databases, Lakehouse technologies, and AI orchestration frameworks.
• Strong technical leadership and stakeholder communication skills.

The pay range that the employer in good faith reasonably expects to pay for this position is $37.91/hour - $59.23/hour. Our benefits include medical, dental, vision and retirement benefits. Applications will be accepted on an ongoing basis.

Tundra Technical Solutions is among North America’s leading providers of Staffing and Consulting Services. Our success and our clients’ success are built on a foundation of service excellence.

We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.

Qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable law, including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act.

Unincorporated LA County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: client provided property, including hardware (both of which may include data) entrusted to you from theft, loss or damage; return all portable client computer hardware in your possession (including the data contained therein) upon completion of the assignment, and; maintain the confidentiality of client proprietary, confidential, or non-public information.

In addition, job duties require access to secure and protected client information technology systems and related data security obligations.