AI Full Stack Developer

AI Full Stack Developer

Location: Mumbai

Job Summary

We are looking for a highly skilled AI Full Stack Developer to design, develop, integrate, test, secure, and deploy AI-powered applications and business automation solutions. The role combines AI/ML, Generative AI, full-stack development, data engineering, API integration, workflow automation, cloud infrastructure, cybersecurity, and AI testing.

The candidate will work closely with business and technical teams to identify AI use cases, develop scalable applications, integrate enterprise systems, build intelligent workflows, and deploy secure and reliable AI solutions across the organization.

Key Responsibilities

AI/ML & Gen AI Development

• Develop AI/ML solutions using Python, LLMs, Generative AI, NLP, and modern AI frameworks.
• Integrate models and APIs including OpenAI, Azure OpenAI, Gemini, and Anthropic.
• Design and implement Prompt Engineering strategies for reliable and task-specific AI outputs.
• Build RAG-based applications using embeddings, vector databases, LangChain, and LlamaIndex.
• Develop AI Agents using function/tool calling and tool-based AI architectures.
• Implement Document AI and OCR solutions for structured and unstructured business documents.
• Design AI evaluation frameworks covering response accuracy, hallucination detection, reliability, and performance.
• Integrate AI models with enterprise applications through APIs and production-ready workflows.Full Stack Application Developer
• Develop scalable backend applications using Python/FastAPI or Node.js/TypeScript.
• Design and develop REST APIs, microservices, webhooks, background jobs, and queue-based processes.
• Build secure authentication and authorization systems using RBAC, OAuth 2.0/OIDC, and JWT.
• Develop responsive web applications using React, Next.js, TypeScript, JavaScript, HTML5, CSS3, and Tailwind CSS or equivalent.
• Build dashboards, data visualizations, forms, and responsive user interfaces with appropriate state management and form validation.
• Ensure accessibility and usability across web applications.
• Integrate REST APIs and develop intuitive UI experiences for AI-powered applications.
• Implement AI/LLM functionality and AI-specific UX within business applications.Data, Integration & Automation
• Build ETL/ELT pipelines, data cleaning/transformation, validation, indexing, document processing, and RAG data pipelines.
• Work with advanced SQL, PostgreSQL, REST APIs, JSON, Apache Airflow/equivalent, and vector databases.
• Integrate ERP/CRM, Microsoft Graph API, Google APIs, webhooks, and third-party services.
• Develop workflow automation using Power Automate/equivalent, AI Agents, MCP/tool-based integration, and function calling.Cloud, DevOps & Infrastructure
• Develop and deploy applications using Linux, Git, Docker, Kubernetes, and AWS/Azure/GCP.
• Build CI/CD pipelines using GitHub Actions, GitLab CI, Jenkins, and manage Nginx, DNS, TLS/SSL, and application infrastructure.
• Implement monitoring and logging using Prometheus, Grafana, ELK/OpenSearch, along with backup and disaster recovery processes.
• Work with Terraform, Ansible, Redis, secrets management, network/container security, and basic GPU infrastructure.Cybersecurity & AI Security
• Implement IAM, RBAC, SSO, OAuth/OIDC, Microsoft Entra ID, encryption, API security, and secrets management.
• Apply OWASP, secure coding, vulnerability management, audit logging, DLP, SIEM, and incident response practices.
• Secure AI applications against prompt injection, data poisoning, unauthorized model/data access, and RAG security risks.
• Ensure appropriate security, compliance, and access controls across applications and AI systems.Testing & Quality
• Perform manual, automation, API, regression, integration, performance, and security testing.
• Use Postman, Playwright/Selenium, Python/JavaScript, and SQL for testing and automation.
• Develop AI test datasets and perform prompt testing, RAG evaluation, hallucination testing, AI response testing, and accuracy evaluation.
• Integrate testing into CI/CD workflows and maintain test automation using Git.Business & Product Collaboration
• Gather requirements, analyse business processes, identify AI use cases and automation opportunities, and define functional requirements.
• Create process maps, user stories, documentation, KPIs, and support UAT.
• Work with business and technical teams using Agile/Scrum, Jira, and Confluence.
• Monitor deployed solutions and continuously improve AI models, applications, workflows, data pipelines, and system performance.

Qualification

• Bachelor's or Master's degree in Computer Science, Information Technology, AI/ML, Data Science, Engineering, or a related discipline.
• Certifications/specialization in AI/ML, Cloud, Cybersecurity, or Data Engineering will be an added advantage.Experience
• 2+ Years of experience in software development, AI/ML, full-stack development, automation, data engineering, or related technology roles.
• Strong hands-on experience in developing and deploying production-grade AI-powered applications will be preferred.