Senior Software Engineer

Role & responsibilities

• Lead architecture and implementation decisions across cloud infrastructure, backend services, APIs, and frontend applications
• Own AWS architecture decisions including compute, networking, IAM, security, cost optimization, scalability, and reliability planning
• Drive containerization and orchestration practices using Docker and Kubernetes, ideally within EKS based environments
• Provide technical oversight and code review for frontend and UI development, establishing engineering standards, component design practices, and maintainable application structure
• Design and lead development of backend services and REST APIs in Python with a strong focus on scalability, reliability, and maintainability
• Partner with data science and analytics teams to productionize AI, ML, and LLM based capabilities into the SaaS platform
• Champion AI assisted development practices using GitHub Copilot and Claude Code to improve engineering productivity, code quality, documentation, and automation workows
• Establish standards and guardrails for the responsible use of AI assisted coding tools, including considerations for security, IP, and data privacy
• Lead code reviews, technical design discussions, and implementation planning across the engineering team

Required Technical Skills

• Deep hands on experience with AWS cloud services including EC2, ECS or EKS, IAM, S3, Lambda, VPC, networking, and cloud security fundamentals
• Strong experience with Docker and Kubernetes, preferably with production deployments on AWS
• Strong backend development experience in Python with hands on expertise in designing and building scalable services and REST APIs
• Strong prociency in modern frontend and UI development, preferably Angular, sucient to guide architecture, review code, and establish development standards
• Strong working knowledge of SQL and relational database design, including schema design, query optimization, and data access strategies
• Experience designing and implementing CI/CD pipelines using tools such as Azure DevOps, GitHub Actions, or Jenkins
• Strong understanding of microservices architecture, modular application design, and distributed systems fundamentals
• Experience using AI assisted development tools such as GitHub Copilot and Claude Code in professional engineering workows
• Strong understanding of secure coding, code quality standards, production support expectations, and system maintainability

Preferred Skills and Experience

• Exposure to

  Java

  and Spring Boot is a plus
• AWS certication such as Solutions Architect Associate or Professional is preferred Experience with MongoDB or Redis for caching and specialized data access use cases
• Familiarity with MLOps and integrating AI or ML services such as SageMaker or Bedrock into production systems
• Experience establishing engineering standards, AI assisted development practices, or usage guardrails for a broader team
• Experience working in enterprise SaaS, B2B, or cloud native platform engineering environments Domain exposure to energy, industrial, or oil and gas platforms is a plus
• Experience supporting technical interviews, hiring decisions, onboarding, and team capability development.