Solutions Architect

4 weeks ago

Indianapolis, United States Alldus Full time

Job Title: AI Solutions Architect

Location: On site/Hybrid Indianapolis, Indiana

Work Authorization: US Citizen/GC

Company: Our client who are revolutionizing the energy sector are hiring an AI Solutions Architect to join their team in Indianapolis. The successful candidate will play a critical role in configuring and deploying state-of-the-art AI solutions tailored to address the distinctive requirements of the company's key customers.

Responsibilities: As the AI Solutions Architect, you will engage with customers post-sales to design and execute full-stack AI solutions, ensuring alignment with functional and performance criteria. You will lead architecture and engineering discussions to showcase the capabilities of the Platform and its integration with current systems. Develop scalable and reusable reference architectures to streamline solution delivery. Generate specifications, documentation and technical procedures, enriching user support materials. Identify and address technical risks to guarantee project success. Support production AI applications by monitoring and executing processes as required. Collaborate with engineering and product teams to incorporate customer feature requests into core product offerings.

Skillset: Bachelor's degree in engineering, computer science or similar. Experience with Large Language Models, Generative AI, etc. At least five years experience working as a Solution Architect in system/data integration, development or enterprise/cloud software implementation. Expert knowledge of enterprise architecture and application integration. Proficient in Big Data, Distributed Systems, and Cloud Architectures (AWS, Azure, GCP). Skilled in Python, JavaScript and/or Java programming languages. Hands-on experience with relational and NoSQL databases. Advanced proficiency in Postgres and Cassandra is a bonus. Familiarity with Hadoop, Spark, and Cloud databases (Snowflake, BigQuery, Redshift, Databricks) and stream processing frameworks (Kafka, Kinesis). Understanding of container-based deployments using Kubernetes or OpenShift. Experience in designing and managing DataOps and MLOps in Production environments.

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