Summary
✨ AI‑Generated
A senior engineering opportunity focused on building scalable production AI and machine-learning systems. You will develop Python backends, build and optimize data pipelines, train and deploy models, integrate generative AI, and automate secure cloud infrastructure using infrastructure-as-code.
Highlights
Senior engineering role combining machine learning, generative AI, backend development, data engineering, and cloud infrastructure. The position offers the opportunity to build scalable production AI systems, work with foundation models, automate infrastructure, and deliver end-to-end intelligent solutions.
Description
Job Overview
We are seeking a highly skilled Senior Engineer to design and build scalable, data-driven AI/ML and Generative AI solutions.
You will leverage foundation models, build robust data pipelines, and automate secure cloud infrastructure using Terraform.
This role combines backend engineering, data science, and modern DevOps to deliver production-grade intelligent systems.
Core Responsibilities
AI/ML & Generative AI DevelopmentBuild, train, evaluate, and deploy production machine learning models.Integrate Generative AI applications via AWS Bedrock using prompt engineering and inference orchestration.Select and tune foundation models optimized for specific business use cases.Software & Data EngineeringDesign, develop, and maintain clean, scalable Python-based backend systems.Optimize data ingestion and processing pipelines for structured and unstructured data.Manage and query high-performance SQL and NoSQL data stores.Cloud Infrastructure & DevOpsArchitect cloud-native, highly available systems using AWS services (SageMaker, Bedrock, Lambda, ECS/EKS).Provision and manage infrastructure as code (IaC) using Terraform.Implement CI/CD pipelines, automated testing, logging, monitoring, and cost-optimization strategies.Leadership & CollaborationCollaborate with cross-functional teams to translate business requirements into technical solutions.Mentor junior engineers, conduct thorough code reviews, and drive architectural decisions.Create detailed technical designs, system documentation, and operational runbooks.
Qualifications & Skills
Educational Requirements
Engineering Degree – BE, ME, BTech, MTech, BSc, or MSc in Computer Science or a related field.Technical certifications in AWS, Terraform, or Machine Learning are highly desirable.
Mandatory Technical Skills
Experience: 6–10 years of overall software engineering experience, with 7+ years in a senior or specialized role.Python Mastery: Expert proficiency in Python for backend development, data processing, and ML workflows.Data Science & ML Frameworks: Deep experience in feature engineering and model evaluation using Scikit-learn, PyTorch, or TensorFlow.AWS Cloud Ecosystem: Strong hands-on experience with EC2, S3, Lambda, ECS/EKS, RDS, and SageMaker.Generative AI: Practical knowledge building and operationalizing apps via AWS Bedrock.Infrastructure as Code: Proven capability provisioning environments utilizing Terraform.Containerization: Familiarity with Docker, Kubernetes, and modern DevOps environments.
Good-to-Have Skills (Preferred)
Experience with clinical, biomedical, or healthcare NLP use cases.Familiarity with healthcare data standards, terminologies, and ontologies.Experience deploying ML/NLP solutions in regulated production environments.Knowledge of distributed systems, cloud-native data warehouses, and large-scale data architectures.Proven track record working in Agile product development teams.
