Full Stack AI Platform Lead at PRODAPT NORTH AMERICA INC

Chennai, tamil nadu, India -

Full Time

Start Date

Immediate

Expiry Date

14 Jan, 26

Salary

0.0

Posted On

16 Oct, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

React, Next.js, Remix, TailwindCSS, JavaScript, TypeScript, Python, FastAPI, REST APIs, Microservices, TDD, Clean Architecture, Prompt Engineering, Docker, Kubernetes, Terraform, AWS

Industry

technology;Information and Internet

Description

Overview We are seeking a versatile and highly skilled Full Stack AI Platform Engineer to design, develop and deploy intelligent, scalable and cloud-native applications. This role blends frontend and backend development with applied AI engineering and DevOps practices. The ideal candidate will have hands-on experience across the stack with a strong understanding of generative AI workflows, microservices architecture, and cloud automation. Responsibilities Frontend Development Build responsive and performant Single Page Applications (SPAs) using React frameworks like js or Remix. Design intuitive UIs that support generative AI interactions, including streaming (SSE) and real-time updates. Rapidly prototype and iterate on UI concepts in collaboration with clients and stakeholders. Utilize modern styling tools like TailwindCSS to enhance development efficiency. Backend Development Develop scalable backend services using Python and FastAPI, following Microservices Architecture (MSA) Build and maintain RESTful APIs and support MCP (Multi-Channel Processing) server/client implementations. Apply Test-Driven Development (TDD) and Clean Architecture principles to ensure code quality and maintainability. Applied AI Engineering Design backend systems optimized for generative AI, including streaming responses and LLM orchestration. Implement and refine prompt engineering strategies (e.g., few-shot, CoT, RAG). Integrate guardrails and safety mechanisms to ensure responsible AI behavior. Collaborate with AI/ML teams to embed intelligent features into platform components. DevOps & Cloud Automation Manage containerized deployments using Docker Compose and Kubernetes. Automate infrastructure provisioning using Terraform. Support CI/CD pipelines and ensure smooth deployment across environments. Operate within AWS, Azure, or other public cloud platforms with a strong understanding of cloud-native services. Soft Skills: Strong problem-solving and analytical thinking. Excellent communication and collaboration skills. Ability to work in a fast-paced, agile environment with cross-functional teams. Ability to empathize with customer challenges and engage in conversations. Defining technical requirements based on business needs and conveying them to customers. Effectively communicating complex technical concepts to both technical and non-technical audiences. Correctly understanding the feasible requirements and limitations of AI and educating customers. Building close relationships with customers and understanding their requirements. Requirements Required Skills: Frontend: React, Next.js/Remix, TailwindCSS, JavaScript/TypeScript, SSE/WebSockets. Backend: Python, FastAPI, REST APIs, Microservices, TDD, Clean Architecture. AI Engineering: Prompt engineering, streaming AI responses, guardrails, LangChain/OpenAI/Hugging Face. DevOps: Docker, Kubernetes, Terraform, CI/CD, AWS/Azure fundamentals. Preferred Qualifications: Experience with vector databases, LLM orchestration frameworks, and real-time AI pipelines. Familiarity with GitOps, monitoring tools and security best practices. Contributions to open-source projects or a strong personal portfolio. Cloud certifications (AWS/Azure) or DevOps certifications are a plus.

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Responsibilities

The Full Stack AI Platform Lead will design, develop, and deploy intelligent, scalable, and cloud-native applications, blending frontend and backend development with applied AI engineering and DevOps practices. Responsibilities include building responsive SPAs, developing scalable backend services, and collaborating with AI/ML teams to integrate intelligent features.