Software Engineer

• Translate functional requirements into system requirements
• Develop web-based applications using coding standards and a continuous Build-Integrate-Test Agile approach
• Build basic code for assigned modules and features using available technology stacks and programming languages
• Design and develop basic database solutions
• Apply troubleshooting and debugging concepts
• Work with Configuration Management tools and enforce CM practices
• Adhere to organizational QA standards
• Understand and address performance bottlenecks, production infrastructure, interfaces, and dependencies
• Design, build, and maintain LLM-powered solutions, custom GPTs, and domain-specific assistants
• Develop and optimize prompts, system instructions, and context strategies
• Implement prompt chaining, tool calling, and basic agentic workflows
• Build and support Retrieval-Augmented Generation pipelines using vector databases
• Evaluate, test, and improve LLM outputs using quality and safety criteria
• Apply responsible AI principles, safety guardrails, and governance standards
• Develop full stack AI-enabled applications, backend services, APIs, and UI integrations
• Integrate LLM capabilities into existing enterprise applications
• Build reusable services and components for AI features
• Debug and resolve application or AI-related issues
• Develop and deploy AI solutions on Azure and/or AWS
• Support CI/CD pipelines for application and AI workloads
• Assist with MLOps workflows including model versioning, deployment, and monitoring
• Ensure production solutions are secure, reliable, and cost-aware
• Collaborate with onshore leads, offshore teams, business stakeholders, customers, supervisors, team members, business analysts, and business teams

• 3–5 years of overall software engineering experience
• Strong full stack development background
• Proficiency in Python and solid programming fundamentals
• Hands-on experience with LLMs, Generative AI, and prompt engineering
• Experience creating or customizing GPT-based solutions
• Familiarity with RAG architectures and vector databases
• Cloud experience with Azure and AWS
• Basic understanding of MLOps, DevOps, and production support practices
• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field preferred as a good-to-have qualification
• Frontend experience with modern frameworks is a plus

• Equal Opportunity Employer commitment and inclusive workplace
• Environment that respects, supports, and inspires all individuals
• Diversity and inclusion initiatives
• Exposure to AI/ML, Generative AI, LLM, cloud, DevOps, and MLOps technologies