What are the responsibilities and job description for the AI Solutions Architect (RWC) position at CultureFit Technology Staffing?
Job Description
Job Summary :
We are seeking an experienced professional to join our AI Solution Architecture team (post-sales). In this customer-facing role, you will have the opportunity to design, develop, and deploy custom and pre-built Enterprise AI applications using the AI Platform. The AI product suite is entirely data-driven, so a great candidate will have a passion for acquiring, analyzing, and transforming data to generate insights with advanced analytics. This role is hands-on and requires a perfect combination of a "big picture," solution-oriented mindset, and solid implementation skills.
Key Responsibilities :
Engage directly with customers in a post-sales capacity to configure and implement a full-stack AI solution according to functional and performance requirements
Drive discussions on architecture and engineering to articulate the capabilities of the company Platform and its interoperability with existing systems
Design and implement reference architectures to deliver scalable and reusable solutions
Develop new specs, documentation, and participate in the development of technical procedures and user support guides
Assess technical risks and come up with mitigation strategies
Collaborate with internal engineering and product teams to incorporate customer feature and enhancement requests into core product offerings
Travel to customer sites (up to 30%)
Required Skills and Experience :
Bachelor's degree in engineering, computer science, or related fields
5 years of experience (8 years for Senior AI SA) with system / data integration, development, or implementation of enterprise and / or cloud software
Deep understanding of enterprise architecture and enterprise application integration (File, API, Queues, Streams)
Extensive hands-on expertise in Big Data, Distributed Systems, and Cloud Architectures (AWS, Azure, GCP)
Demonstrated proficiency with Python, JavaScript, and / or Java
Experience with relational and NoSQL databases (any vendor)
Solid understanding of data modeling best practices
Strong organizational and troubleshooting skills with attention to detail
Strong analytical ability, judgment, and problem-solving techniques
Excellent verbal and written communication and presentation skills
Expertise in Postgres, Cassandra
Experience with stream processing frameworks (Kafka, Kinesis)
Experience with container-based deployments using Kubernetes or OpenShift
Experience designing and maintaining DataOps and MLOps in Production environments
Working knowledge of Machine Learning algorithms
Familiarity with Commercial LLMs, including a comprehensive understanding of their integration, customization, and management
Familiarity with vector databases (e.g., PGVector, FAISS) for efficient embedding storage and retrieval in RAG applications
Familiarity with AI / ML-related technologies and tools (MLFlow, KubeFlow, AWS SageMaker, Azure MLStudio)
Experience with Information, Network, & Infrastructure Security concepts
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