Sr Software Engineer

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 workflows

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

Mentor junior and mid level engineers on cloud engineering, frontend architecture, backend design, and modern development practices

Champion CI/CD, automated testing, DevOps practices, and release quality across the development lifecycle

Collaborate with product managers, architects, engineering leadership, and cross functional stakeholders to translate roadmap requirements into scalable technical solutions

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 proficiency in modern frontend and UI development, preferably Angular, sufficient 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 workflows

Strong understanding of secure coding, code quality standards, production support expectations, and system maintainability

Exposure to Java and Spring Boot is a plus

AWS certification 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.

6 to 9 years of professional software engineering experience, including meaningful experience influencing architecture, mentoring engineers, and driving technical decisions.

For roles outside USA:

Bachelor's Degree in Computer Science or “STEM” Majors (Science, Technology, Engineering and Math) with basic experience.

AWS, Docker, Kubernetes, EKS, IAM, networking, CI/CD

Python, REST APIs,Java (good to have)

Angular preferred, React or Vue also considered, TypeScript, HTML, CSS

SQL and relational databases (must have), NoSQL databases such as MongoDB or DynamoDB (working knowledge)

Git, Azure DevOps, GitHub Actions, Jenkins

AI assisted development tools such as GitHub Copilot and Claude Code

Demonstrates strong technical leadership and ownership across architecture and delivery Provides mentorship and technical guidance to junior and mid level engineers. Drives engineering best practices in coding, testing, documentation, DevOps, and responsible AI assisted development.

Leads architecture reviews and technical discussions with clarity and sound judgment.

Builds effective working relationships across product, engineering, data science, analytics, and stakeholder teams

Contributes to hiring, onboarding, and long term team capability building