Job Title: Solution Architect AI/ML
Experience: 812 Years
Location: [Hybrid/Remote] for Bangalore
Employment Type: Full-time
About the Role
We are seeking a Solution Architect with deep AI/ML expertise, strong hands-on experience in Node.js and Python, and the ability to own end-to-end product/solution delivery. The ideal candidate is both a technology strategist and a hands-on problem solver who can design, architect, and implement scalable systems independently.
Key Responsibilities
- Lead solution architecture for AI/ML-driven products and enterprise applications.
- Work hands-on to design, develop, and deploy scalable AI/ML systems using Python and related frameworks.
- Build robust backend architectures using Node.js and modern cloud-native design patterns.
- Translate business requirements into scalable, secure, and maintainable technology solutions.
- Collaborate with stakeholders to define technical roadmaps, system design, data workflows, and integration strategies.
- Own full project lifecycle: requirement analysis, solution design, architecture, development, deployment, and optimization.
- Review code, enforce best engineering practices, and ensure high-quality deliverables.
- Stay updated with emerging AI trends, tools, and frameworks; drive innovation with practical solutions.
Required Skills & Experience
- 812 years of overall technology experience, with strong architecture leadership.
- Proven experience designing end-to-end AI/ML systems, pipelines, and models.
- Hands-on expertise in Python (ML/TensorFlow/PyTorch/Scikit-learn).
- Strong backend development knowledge using Node.js.
- Strong understanding of microservices, APIs, distributed systems, and cloud architectures (AWS/Azure/GCP).
- Ability to design large-scale data processing workflows, ETL pipelines, and ML model deployment.
- Deep understanding of scalability, performance, security, and DevOps processes.
- Excellent communication, stakeholder management, and documentation skills.
- Ability to work independently and lead entire project delivery.
Good to Have
- Experience with LLMs, Generative AI, RAG, NLP-based solutions.
- Exposure to MLOps tools (Kubeflow, MLflow, Airflow, Docker, Kubernetes).
- Experience in solutioning for enterprise clients or large-scale systems.
