Lead Software Engineer

Primary Responsibilities:

• Design, develop, test, and maintain enterprise applications across all phases of the AI Software Development Life Cycle (AI-SDLC), including requirements analysis, technical design, implementation, deployment
• Build and deliver scalable, secure, and high-performing applications and APIs, ensuring alignment with enterprise architecture and engineering standards
• Design and implement microservices-based, cloud-native solutions with a focus on scalability, resiliency, and operational readiness
• Collaborate with product owners, architects, and cross-functional teams to translate business requirements into well-defined technical solutions and implementation plans
• Develop backend services using Java (Spring Boot), and/or Python, ensuring maintainable, testable, and high-quality code
• Develop front end applications using Reacts/Angular/Next.js
• Design, develop, and integrate RESTful APIs and enterprise system integrations to support end-to-end business workflows
• Design and implement AI-powered solutions to address complex business problems, leveraging modern AI/GenAI technologies
• Build and operationalize Agentic AI solutions, including multi-step orchestration, tool integration, and workflow automation
• Develop and implement RAG (Retrieval Augmented Generation) pipelines, enabling knowledge-driven and context-aware AI applications
• Participate in and contribute to the AI Product Development Lifecycle (AI PDLC), including model development, evaluation, deployment, and monitoring of AI solutions
• Implement and maintain CI/CD pipelines using GitHub Actions, enabling automated build, test, and deployment processes
• Manage infrastructure provisioning using Infrastructure as Code (Terraform) and support cloud-native deployment models
• Develop and deploy applications using Docker and Kubernetes (AKS), ensuring scalability and high availability
• Manage artifact lifecycle using JFrog / Artifactory and support efficient build and release processes
• Ensure adherence to Secure practices, including secure coding, vulnerability management, and compliance with enterprise standards
• Participate in Agile/Scrum ceremonies, including sprint planning, daily stand-ups, and retrospectives, ensuring timely and high-quality delivery
• Ensure solutions meet quality, performance, and security standards, including code reviews, testing, and monitoring
• Troubleshoot and resolve complex production issues, perform root cause analysis, and implement preventative fixes
• Provide technical leadership and mentorship through code reviews, design guidance, and knowledge sharing
• Contribute to architecture discussions, design decisions, and engineering standards across the team
• Collaborate with stakeholders to drive continuous improvement, innovation, and adoption of modern technologies
• Identify opportunities to automate processes, reduce technical debt, and improve system performance and efficiency
• Works with less structured, more complex issues
• Serves as a resource to others
• Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so

Qualifications - External

Required Qualifications:

• Graduate degree or equivalent experience
• 6+ years of experience over API design, service integration, and backend system engineering
• 4+ years of hands-on experience implementing CI/CD pipelines using GitHub Actions, along with Terraform-based infrastructure provisioning 
• 4+ years of solid Azure Cloud experience, building and operating cloud-native applications
• Hands-on experience building AI-enabled systems using Agentic AI architectures (multi-step orchestration, tool usage), RAG pipelines with vector search and knowledge grounding
• Experience operating in Agile/Scrum teams with consistent delivery ownership
• Working experience with LLM orchestration, prompt engineering, and AI workflow automation
• Solid experience building API-driven platforms, reusable frameworks, and enterprise-grade integrations
• Solid experience with Docker and Kubernetes (AKS) for containerized deployments, JFrog / Artifactory for artifact lifecycle management
• Deep backend engineering experience with Java (Spring Boot) and Python, delivering production-grade systems
• Working knowledge of the AI PDLC lifecycle (build, evaluate, deploy, monitor)
• Proven expertise in designing and scaling microservices-based and distributed architectures with Solid focus on resilience, latency, and throughput
• Proven exposure to frontend frameworks (React/Angular/Next.js) to support end-to-end solution delivery 
• Solid proficiency in Python for AI pipelines, automation, and agent workflows
• Proven ability to Lead technical initiatives and influence architecture decisions, Mentor engineers and elevate team engineering standards
• Proven ability to collaborate effectively across Product, Infra, DevOps, and Architecture
• Demonstrated solid engineering discipline Clean, testable, maintainable code, Debugging, performance tuning, and system optimization
• Demonstrated solid communication, ownership mindset, and problem-solving skillsRole & responsibilities