Tech Lead - AWS Backend Integration_Sparity_Hyderabad

Dear All,

Greetings From Sparity..!!

Role: Technical Lead Backend and Integration

Location: Offshore – India

Experience: 9 to 12 yrs

Tech Stack: Python, Java, Node.js, AWS (Lambda, API Gateway, AppSync, Step Functions, EventBridge, SQS, SNS), SQL and Stored Procedures, MongoDB, AI-Assisted Software Development

Working Knowledge: EKS, ECS, Docker, OpenShift, VPC, RDS, Security Groups, Terraform, GitHub, Jenkins, GitHub Actions, encryption, IAM

Role Overview

We are looking for a Technical Lead to own the design and delivery of backend and integration services on AWS. You will lead a team building serverless, event-driven APIs and integrations using Python, Java, and Node.js, set engineering standards, and act as a hands-on technical leader who works with the Manager, the Data Engineering and UI/UX leads, and client stakeholders to turn requirements into resilient, well-tested services.

Key Responsibilities

• Lead design and development of backend and integration services in Python, Java, and Node.js
• Design serverless and event-driven solutions on AWS using Lambda, API Gateway, AppSync, Step Functions, EventBridge, SQS, and SNS
• Define API contracts and integration patterns, including AppSync and API Gateway interfaces consumed by the Angular front end
• Own database design and tuning for SQL, stored procedures, and MongoDB workloads that support the services
• Define technical approach, coding standards, and engineering best practices for the backend team
• Lead technical design reviews and code reviews, and mentor Senior Software Engineers
• Own SDLC quality across design, configuration, testing, debugging, implementation, and support, and ensure automated tests are part of the definition of done
• Work with the Automation Engineer to build API and integration test coverage, and cross-train engineers on basic test automation
• Collaborate with the Data Engineering lead on shared data stores, events, and integration points
• Apply working knowledge of ECS, Terraform, GitHub, Jenkins, GitHub Actions, IAM, and encryption to build and deploy services securely
• Drive responsible use of AI-assisted development tools within the team
• Lead incident response, root-cause analysis, and long-term reliability improvements

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, Information Technology, or a related field
• 9 to 12 years of software engineering experience, with significant depth in backend and integration development
• Expert-level proficiency in Python, with strong working proficiency in Java and/or Node.js
• Deep hands-on expertise with AWS Lambda, API Gateway, and AppSync (must haves), and strong experience with Step Functions, EventBridge, SQS, and SNS
• Hands-on knowledge of SQL and stored procedures, and experience with MongoDB
• Experience designing event-driven, asynchronous, and API-based integrations
• Experience across the full software development lifecycle: design, configuration, testing, debugging, implementation, and support of large-scale, business-centric, process-based applications
• Working awareness of EKS, ECS, Docker, OpenShift, VPC, RDS, Security Groups, Terraform, GitHub, Jenkins, GitHub Actions, encryption, and Identity and Access Management (IAM); working knowledge of ECS and Terraform is a must have
• Experience leading technical projects or small teams
• Strong written and verbal communication skills for working with cross-functional and client stakeholders

AI Knowledge & AI-Assisted Development (Required)

• Good understanding of AI/LLM models and how they can be applied to accelerate delivery, including prompt engineering
• Strong, demonstrated use of AI development tools such as Devin AI, Cursor, and Claude Skills across the development lifecycle: design, coding, testing, review, and documentation
• Able to define and enforce team-level standards for responsible AI-assisted coding, including validation rigor, security scanning of AI-generated code, and avoiding data leakage in prompts
• Able to identify where AI-driven automation can meaningfully improve engineering velocity, code quality, or operational efficiency, and lead adoption within the team
• Understanding of secure and compliant AI tool usage, including never entering PHI, member data, client-specific credentials, or other sensitive information into prompts or external AI tools

Preferred Qualifications

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