Sr. AI Engineer with Snow flake and data bricks is MUST - Overall 12+yrs

Posted Yesterday
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Atlanta, GA, USA
In-Office
Senior level
Logistics • Transportation
The Role
Design and productionize LLM-powered applications (RAG, agentic workflows, prompt pipelines). Integrate external model APIs, deploy models as scalable low-latency services, build data pipelines for retrieval, evaluation and fine-tuning, and establish observability for performance and safety.
Summary Generated by Built In
Company Description

We provide Recruitment and Staffing services to many industries and domain through our innovative and customized solutions and passionate commitment to research. Ability to understand the hiring strategies, availability of talent and compensation benchmarking makes us proud hiring partner for various industries. We work as trusted business partners and always strive to deliver the most value and highest return on investment for our clients. We are highly trained business professionals with strong understanding of clients need. We work closely with the leading staffing trade associations, training, and research organizations to ensure we are knowledgeable of the latest industry trends and technologies.

Job Description

 NOTE: Candidate must have prior experience with below clients:

Ex-Amazon
Apple
Facebook 
Netflix
Google 
Key Responsibilities:

Build AI Systems: Design and deliver LLM-powered applications, including agentic multi-step workflows, Retrieval-Augmented Generation (RAG) systems, and structured prompt pipelines. 
Productionize AI: Transform AI prototypes into reliable services by packaging models behind APIs, deploying to cloud infrastructure, and ensuring low-latency scalability. 
Integrate APIs: Consume and manage external model APIs (e.g., OpenAI, Anthropic, Hugging Face) while handling rate limits, streaming, and cost control. 
Evaluate and Monitor: Establish evaluation pipelines and observability to monitor performance, handle drift, and ensure outputs meet safety and accuracy standards. 
Data Management: Own data processing pipelines for retrieval, evaluation, and fine-tuning using proprietary company data. 

 

Regards,

Mohammed ilyas,

PH - 229-264-4024 or Text - 229-469-1455 or you can share the updated resume at Mohammed@vtekis. com

Additional Information

All your information will be kept confidential according to EEO guidelines.

Skills Required

  • 12+ years overall experience
  • Prior experience with Amazon, Apple, Facebook, Netflix, or Google
  • Hands-on experience with Snowflake
  • Hands-on experience with Databricks
  • Design and build LLM-powered applications including RAG and agentic workflows
  • Experience productionizing models: packaging models behind APIs and deploying to cloud for low-latency scalability
  • Experience integrating external model APIs (OpenAI, Anthropic, Hugging Face) and handling rate limits/streaming/costs
  • Establish evaluation pipelines and observability to monitor model performance and drift
  • Build and own data processing pipelines for retrieval, evaluation, and fine-tuning using proprietary data
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The Company
HQ: Auburn Hills, MI
4,509 Employees
Year Founded: 2007

What We Do

Syncreon delivers tailored, scalable and progressive solutions to customers in more than 100 global locations. The company has managed supply chain synergies for global automotive and technology premier brands for more than 60 years. We partner with customers to provide specialized logistics, operational excellence and value-added solutions in: warehouse management services, fulfilment, inbound to manufacturing, export packing, aftermarket services, reverse and repair, and transport management. syncreon specializes in helping customers create unique and inventive 3PL and 4PL operations that adapt as the industry and marketplace evolve. Our solutions are based on the lifecycle phases of planning, sourcing, making, delivering and returning products. As a global company, syncreon strategically locates its facilities in close proximity to our customers, in order to increase efficiencies and optimize supply chains through performance improvement.

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