AI/ML Solutions Architect (PostgreSQL)
Auto req ID 1648165BR SR Number DBS/DBS-/2026/2819237 Designation Contractor Location Ohio City Ottawa No. of Positions 1 Job Description (Posting). AI/ML Solutions Architect (PostgreSQL) Job Summary This role is responsible for architecting and designing advanced artificial intelligence and machine learning solutions, leveraging a broad suite of data engineering and modeling technologies. The position drives strategic technical decisions, guides teams in implementing scalable AI/ML systems, and ensures alignment with organizational standards and client requirements. They play a pivotal role in integrating modern data platforms and delivering innovative solutions that address complex business challenges. (1.) Key Responsibilities 1. Architect end-to-end AI/ML solutions using Python, TensorFlow, PyTorch, and scikit-learn, ensuring robust model development and deployment frameworks. 2. Design scalable data pipelines and real-time processing systems utilizing Apache Spark, Kafka, and PostgreSQL to support machine learning workflows. 3. Guide the team in implementing advanced ML models, including deep learning, NLP, and time series forecasting, using tools such as XGBoost, LightGBM, and Spark MLlib. 4. Oversee integration of data engineering platforms like Apache Airflow, DataBricks, and RabbitMQ to optimize data ingestion, transformation, and orchestration for AI/ML projects. 5. Ensure technical excellence by advocating best practices in model validation, performance optimization, and reproducibility across Python, R, and SQL-based environments. 6. Collaborate with stakeholders to gather requirements, translate business needs into technical specifications, and deliver tailored AI/ML solutions that meet quality and compliance standards. 7. Mentor and coach team members in advanced AI/ML concepts, fostering continuous learning and adoption of emerging technologies within the skill cluster. 8. Architect and implement RESTful API integrations to enable seamless communication between AI/ML components and external systems, ensuring scalable, secure, and efficient data exchange across diverse enterprise environments. Skill Requirements 1. Expert Proficiency In Ai/Ml Model Development, Including Classical Machine Learning, Deep Learning, Nlp, And Time Series Forecasting. 2. Excellent Knowledge Of Python, R, Sql, And Bash For Data Analysis, Model Experience 9-11 Years Qualification Bachelor of Technology/ Engineering Other Requirement Job Location/Client Location (with City & State) Ohio, Maryville Honda Office (Onsite) Role Overview The AWS Senior Data Architect is responsible for designing, implementing, and managing scalable, secure, and high-performing data solutions on AWS. This role involves working closely with business stakeholders, data engineers, and cloud architects to modernize enterprise data platforms, enable advanced analytics, and ensure governance and compliance. Key Responsibilities Solution Architecture Design and implement cloud-native data architectures (data lakes, warehouses, lakehouse models). Define best practices for data ingestion, transformation, and storage using AWS services (Redshift, Glue, S3, EMR, Athena, Kinesis). Data Strategy & Governance Establish data modeling standards and metadata management. Ensure compliance with data security, privacy, and governance policies. Collaboration Partner with business leaders to align data solutions with organizational goals. Work with engineering teams to optimize pipelines and analytics workloads. Innovation Drive adoption of emerging technologies (Databricks, Snowflake, GenAI-driven workloads). Lead modernization initiatives from legacy systems to AWS cloud. Leadership Provide technical guidance and mentorship to data engineers and architects. Act as a trusted advisor for customers on their cloud journey. ️ Required Skills & Experience Technical Expertise Strong knowledge of AWS ecosystem (Redshift, Glue, S3, Lambda, DynamoDB, etc.). Experience with big data frameworks (Spark, Kafka, Hive). Proficiency in SQL and Python for data engineering tasks. Architecture & Modeling Hands-on experience with data lakehouse and medallion architecture. Strong background in data modeling, ETL/ELT design, and performance optimization. Professional Experience 8–12 years in data architecture, with at least 5 years in cloud-native solutions. Proven track record of leading enterprise-scale data modernization projects. Soft Skills Excellent communication and stakeholder management. Ability to translate business needs into technical solutions. ✅ Preferred Qualifications AWS Certified Solutions Architect – Professional or AWS Certified Data Analytics – Specialty. Experience with multi-cloud environments (Azure Databricks, GCP BigQuery). Familiarity with AI/ML-driven data pipelines.