Senior Data Engineer (AI & ML)

We are looking for highly skilled and experienced professionals for the role of Senior Data Engineer (AI & ML) with strong expertise in enterprise data platforms, artificial intelligence, machine learning, and large-scale analytics solutions. The ideal candidate should possess deep technical knowledge in modern data engineering and AI/ML ecosystems, along with experience delivering scalable and secure solutions for government or public sector programs.The role requires hands-on engineering expertise, architecture understanding, and the ability to work across complex data transformation and AI-driven initiatives.Key ResponsibilitiesData Engineering ResponsibilitiesDesign, develop, and maintain scalable data pipelines and enterprise data platforms. Build robust ETL/ELT frameworks for structured and unstructured data processing. Develop and optimize data ingestion, transformation, and integration workflows. Implement data lakes, data warehouses, and real-time streaming architectures. Ensure data quality, governance, security, lineage, and compliance standards. Work with large-scale datasets from multiple enterprise and government systems. Optimize data storage, processing performance, and scalability.AI/ML ResponsibilitiesDesign, develop, train, and deploy machine learning and AI models for enterprise use cases. Build predictive analytics, NLP, computer vision, recommendation systems, or intelligent automation solutions. Implement MLOps practices for model deployment, monitoring, retraining, and governance. Collaborate with business and domain teams to translate requirements into AI-driven solutions. Evaluate emerging AI technologies and recommend modernization strategies. Develop responsible AI frameworks aligned with governance and compliance requirements. General ResponsibilitiesCollaborate with architects, business teams, analysts, and engineering teams. Provide technical leadership and mentoring to junior engineers and data scientists. Participate in architecture discussions, code reviews, and technical governance. Support cloud migration, modernization, and digital transformation initiatives. Prepare technical documentation, solution designs, and implementation plans. Ensure adherence to security, privacy, and regulatory compliance standards. Job Requirements:·       Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, Engineering, or related field.8+ years of hands-on experience in Data Engineering and AI/ML practices. Data Engineering- Strong expertise in: Python SQL Spark / PySpark Hadoop ecosystem ETL/ELT pipelines Data Warehousing concepts Experience with: Apache Kafka Airflow Databricks Snowflake Big Data technologies Strong knowledge of batch and real-time data processing. ·       AI/ML Engineering: Hands-on experience in: Machine Learning algorithms Deep Learning frameworks NLP and Generative AI concepts Model training and deployment Experience with: TensorFlow / PyTorch / Scikit-learn ML pipelines and MLOps frameworks Model monitoring and optimization Understanding of AI governance, explainability, and responsible AI practices. Cloud & DevOpsExperience with cloud platforms such as: AWS Azure GCP Knowledge of: Docker Kubernetes CI/CD pipelines Infrastructure automation Government/Public Sector Experience (Preferred)Experience working on Government/Public Sector digital transformation projects. Understanding of governance, compliance, security, and large-scale citizen data systems. Exposure to smart governance, public administration, e-governance, or national-scale platforms is an advantage. Preferred SkillsExperience with GenAI, LLMs, Retrieval-Augmented Generation (RAG), or AI copilots. Familiarity with graph databases and knowledge graphs. Exposure to data governance and metadata management tools. Experience with BI and analytics platforms such as Power BI or Tableau. Certifications in Cloud, Data Engineering, or AI/ML are preferred.