<p><p>The Senior Software Engineer AI Integration acts as the critical link between AI and real-world implementation.
This role is responsible for designing, connecting, and delivering robust, end-to-end pipelines that integrate AI models and workflows into scalable, production-grade fintech solutions.</p><p><br/><b>Key Responsibilities : </b><br/><br/></p><p>- Analyze, design, program, debug, and enhance software for AI-driven applications.<br/><br/></p><p>- Develop and maintain robust data and model pipelines, ensuring seamless ML/AI integration.<br/><br/></p><p>- Implement and manage containerized solutions using Docker and orchestration tools (Kubernetes).<br/><br/></p><p>- Utilize Terraform for infrastructure-as-code to manage and scale cloud resources.<br/><br/></p><p>- Collaborate with AI engineers to operationalize models and workflows in production environments.<br/><br/></p><p>- Build and maintain CI/CD pipelines for automated testing, deployment, and monitoring.<br/><br/></p><p>- Write clean, maintainable code with comprehensive testing and debugging.<br/><br/></p><p>- Participate in architectural design sessions and technical decision-making.<br/><br/></p><p>- Prepare documentation for installation, maintenance, and internal training.<br/><br/></p><p>- Work with cross-functional teams (Product, Sales, Training) for successful AI system adoption.<br/><br/></p><p>- Lead or contribute to project planning, estimation, and delivery of AI/DevOps : </b><br/><br/></p><p>- Bachelors or Masters degree in Computer Science, Engineering, or related field.<br/><br/></p><p>- Minimum 5 years of software engineering experience with AI/ML integration and DevOps.<br/><br/></p><p>- Strong programming in Python (plus Java, C++, or Go preferred).<br/><br/></p><p>- Experience building end-to-end ML/AI pipelines and production integration.<br/><br/></p><p>- Proficiency with containerization (Docker) and orchestration (Kubernetes).<br/><br/></p><p>- Hands-on with Terraform and Familiarity with agentic AI frameworks and orchestration tools.<br/><br/></p><p>- Experience with cloud infrastructure (AWS, GCP, Azure) and MLOps practices.<br/><br/></p><p>- Solid understanding of software architecture, design patterns, and SDLC.<br/><br/></p><p>- Excellent problem-solving, communication, and teamwork skills.<br/><br/></p><p>- Experience in Agile or other modern software methodologies</p><br/></p> (ref:hirist.tech)