AI/ML Software Engineer

• Design, build, and deploy AI/ML-powered applications from concept through production.
• Build scalable backend services and APIs using Python and frameworks such as FastAPI.
• Develop responsive and user-friendly frontend applications using React, JavaScript, and TypeScript.
• Design scalable software architecture, reusable components, and appropriate design patterns for AI and non-AI applications.
• Productionize and deploy AI models and inference services using cloud platforms such as AWS, Azure, or GCP.
• Build and maintain MLOps and CI/CD pipelines for application code, models, prompts, and evaluation assets.
• Implement observability using logs, metrics, traces, dashboards, and alerts.
• Define and monitor service-level objectives for latency, availability, accuracy, error rate, and cost.
• Use AI-assisted software development tools to accelerate coding, testing, documentation, and prototyping while maintaining engineering quality.
• Collaborate with product managers, domain experts, data scientists, and software engineers to convert business needs into measurable AI quality goals.
• Participate in architecture reviews, technical design discussions, and production readiness assessments.
• Mentor engineers on AI/ML engineering practices, software architecture, testing, and responsible use of AI tools.
• Stay current with advancements in generative AI, machine learning, cloud technologies, and software engineering practices.

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Software Engineering, or a related field.
• Experience developing and deploying machine learning or AI-powered applications.
• Strong programming experience in Python.
• Experience building production APIs and backend services using FastAPI, Flask, Django, or similar frameworks.
• Strong frontend development experience using React, JavaScript, and/or TypeScript.
• Hands-on experience with LLMs, generative AI, prompt engineering, RAG, or AI agents.
• Understanding of machine learning concepts, model evaluation, data preparation, and inference workflows.
• Experience with cloud platforms such as AWS, Azure, or GCP.
• Experience with containers and deployment technologies such as Docker and Kubernetes.
• Familiarity with CI/CD, infrastructure-as-code, and DevOps practices.
• Experience working with relational and NoSQL databases, such as PostgreSQL, MongoDB, or equivalent.
• Familiarity with vector databases or search technologies, such as PostgreSQL with vector extensions, Pinecone, Weaviate, Milvus, or similar.
• Strong understanding of software architecture, scalability, security, testing, and design patterns.
• Experience developing automated tests and maintaining high-quality, production-ready code.
• Strong analytical, problem-solving, communication, and collaboration skills.

• Remote work / work from home (India)
• Full-time employment