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 **Requirements** * Bachelor's 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