Senior AI Engineer

We are looking for a Senior AI Engineer with strong full-stack engineering and AI solution development expertise to architect, build, and scale enterprise-grade intelligent solutions. This role requires a blend of hands-on technical leadership, solution architecture, and AI implementation experience, with the ability to translate business requirements into secure, scalable, and production-ready applications.
The ideal candidate will bring deep expertise in AI-enabled software engineering, system integration, cloud-native development, and DevOps practices, with a strong focus on accelerated delivery through modern engineering methodologies, automation, and continuous improvement. Experience in deploying AI/ML models into enterprise environments, working across cross-functional teams, and driving innovation while maintaining governance, security, and long-term maintainability will be key to success.
Requirements:
You have 5+ years of experience in software engineering, enterprise application development, or solution architecture, with hands-on exposure to AI/ML-driven solutions.
You bring strong development expertise in technologies such as Python, Java, TypeScript, or Go.
You have practical experience integrating AI or machine learning capabilities into enterprise applications or digital platforms.
You are comfortable working with cloud platforms such as AWS, Azure, or Google Cloud.
You understand APIs, microservices, distributed systems, containerization, and modern integration patterns.
You have experience using AI-assisted development tools and engineering productivity accelerators.
You bring strong experience with Agile delivery, DevOps practices, CI/CD automation, and engineering lifecycle execution.
You understand secure engineering principles, data privacy considerations, and enterprise governance expectations.
You are a structured problem solver with strong communication and stakeholder management skills.
Primary Skills: AI/ML such as AWS/Azure/GCP Solutions Architect, TOGAF-Certified Kubernetes Administrator with exposure to Lean Six Sigma.
Good to have skills / qualifications:
Experience building and scaling machine learning, generative AI, or intelligent automation solutions in production environments.
Familiarity with MLOps, LLM integration, prompt engineering, model monitoring, and AI validation practices.
Experience working within banking, fintech, payments, or other highly regulated industry environments.
An advanced degree in Computer Science, Artificial Intelligence, Engineering, or a related discipline.
Relevant certifications in cloud architecture, enterprise solution design, platform engineering, or AI/ML, such as AWS/Azure/GCP Solutions Architect, TOGAF, or Certified Kubernetes Administrator, with exposure to Lean Six Sigma considered an advantage.
Experience leading engineering transformation, automation initiatives, or enterprise modernization programs.
Demonstrated passion for innovation through open-source contributions, experimentation with emerging technologies, or adoption of modern engineering practices.

Experience
5-6 yrs