Software Engineer II AI & Data Engineering

Devsinc is looking to hire a highly skilled Software Engineer II AI & Data Engineering with 2.5 years of professional experience in building and deploying production-grade AI/ML systems LLM-powered applications and scalable data engineering solutions.

This role requires strong hands-on expertise in AI/ML Engineering MLOps Backend Engineering and Data Engineering with ownership across the complete lifecycle from designing LLM applications RAG pipelines embeddings and inference systems to building ETL/ELT pipelines cloud-native infrastructure and real-time data processing architectures.

Responsibilities:

• Design develop fine-tune and deploy AI/ML models including LLM-powered applications RAG pipelines embeddings vector search architectures and inference systems for real-world business use cases.
• Build and optimize high-performance Python-based APIs microservices and backend services for AI workloads while collaborating with Engineering teams Project Managers and business stakeholders to deliver scalable production-grade AI solutions.
• Design and implement MLOps workflows and cloud-native infrastructure across AWS Azure and GCP including experiment tracking model versioning deployment automation monitoring and model optimization through hyperparameter tuning quantization and inference optimization.
• Design develop and maintain scalable ETL/ELT pipelines for structured and unstructured datasets.
• Build and optimize data transformation cleansing validation and quality frameworks while working with distributed and streaming technologies such as Kafka Spark Kinesis and Pub/Sub for real-time data processing.
• Ensure reliability scalability security and cost optimization across AI and data infrastructure while documenting architecture decisions technical workflows and engineering standards.

• Bachelors degree in Computer Science Software Engineering AI Data Science or related field.
• 2.5 years of hands-on experience in AI/ML Engineering Data Engineering or Backend Systems.
• Strong proficiency in Python and SQL with hands-on experience in production-grade AI/data systems relational/non-relational databases and AI/ML libraries such as PyTorch TensorFlow Scikit-learn Hugging Face Pandas and NumPy.
• Hands-on experience with data engineering frameworks such as Apache Spark Airflow dbt or Databricks.
• Strong understanding of ML fundamentals neural networks NLP model optimization and hands-on experience with LLMs RAG embeddings vector databases and fine-tuning techniques (LoRA PEFT QLoRA).
• Proven experience in deploying AI models through APIs microservices and real-time inference systems along with MLOps tools such as MLflow SageMaker Vertex AI and Weights & Biases.
• Strong exposure to MLOps platforms and cloud ecosystems such as MLflow SageMaker Vertex AI Weights & Biases AWS Azure and GCP for model training deployment monitoring and lifecycle management.
• Proficiency in Docker Kubernetes and CI/CD pipelines for containerization orchestration scalable deployments and production environment management.
• Strong understanding of distributed systems machine learning fundamentals data architecture security and scalable system design.

Required Experience:

IC