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