AI Platform Engineer

Key skills

What you’ll do

• Design and develop an internal enterprise AI platform featuring reusable components, Model Gateways, and RAG platforms. Build high-performance Python applications and AI orchestration services to support both customer projects and future products.

What they’re looking for

• Requires 5-8 years of professional software engineering experience with strong proficiency in Python and RESTful API development. A bachelor's degree in Computer Science or a related field is required, along with experience in containerization and AI frameworks.

Job description

AI Platform Engineer (Product Engineering & Internal Innovation) Location: 8-13-95/77, Opposite National Police Academy Main Gate, Sivarampally, Hyderabad, Telangana 500052 Experience: 6+ Years Employment Type: Full-Time Timing – 9:30 AM KSA time Department: Technology & Innovation Prismberry Technology Prismberry Technologies Pvt. Ltd. is an AI-first IT consulting and digital engineering company specializing in Generative AI, Cloud, Data Engineering, Product Development, SAP, DevOps, Quality Engineering, and IT Staff Augmentation. We partner with global enterprises and GCCs to deliver innovative, scalable, and business-driven technology solutions across India, the USA, and the Middle East. Position Summary The AI Platform Engineer will play a key role in designing, developing, and maintaining TechVisions' internal AI platform and reusable AI components. This role is focused on engineering and platform development rather than customer consulting. The successful candidate will work closely with Cloud, Security, DevOps, Product Engineering, and Pre-Sales teams to develop scalable AI services that support both customer projects and future AI products. Key ResponsibilitiesAI Platform Development Design and develop enterprise AI platform services Build reusable AI APIs and shared platform components Develop AI orchestration services and workflow engines Build Model Gateway services for multiple LLM providers Develop Prompt Management and Prompt Library services Build Retrieval-Augmented Generation (RAG) platforms Implement AI Observability and Monitoring capabilities AI Engineering Develop high-performance Python applications using FastAPI Build Agent-based and Multi-Agent AI systems Design AI pipelines and workflow orchestration services Develop background processing and asynchronous services Build secure REST APIs for enterprise AI applications AI Model Integration & Deployment Integrate and deploy AI models and services including: OpenAI Claude Gemini Groq Ollama vLLM Open-source Large Language Models (LLMs) AI Infrastructure Deploy and manage AI services using Docker and Kubernetes Configure GPU-enabled environments Maintain model serving infrastructure Implement API Gateway integrations Optimize caching and performance for AI workloads Software Quality & Engineering Excellence Write clean, maintainable, and well-documented code Develop unit, integration, and API tests Participate in code reviews Perform performance tuning and optimization Support secure software development practices Required QualificationsEducation Bachelor's degree in Computer Science, Software Engineering, Artificial Intelligence, Information Technology, or a related field. Experience 5-8 years of professional software engineering experience Experience developing production-grade AI applications Strong Python development experience Experience building RESTful APIs Experience working in Agile development environments Required Technical SkillsProgramming & Backend Python FastAPI Async Programming REST APIs Git Databases PostgreSQL Redis Containerization & Infrastructure Docker Kubernetes AI & Machine Learning Experience with one or more of the following: LangChain LangGraph Model Context Protocol (MCP) OpenAI SDK Prompt Engineering Retrieval-Augmented Generation (RAG) Vector Search Embeddings AI Evaluation Frameworks Run:AI Ray Serve (Preferred) AI Infrastructure Exposure to: Ollama vLLM NVIDIA GPU environments CUDA (Basic Knowledge) TensorRT (Preferred) Preferred Qualifications Experience or knowledge in: Cloud Platforms (OCI, Azure, AWS, or Google Cloud) Enterprise Architecture Enterprise Security Identity and Access Management Soft Skills Strong analytical and problem-solving abilities Passion for AI and emerging technologies Ability to work collaboratively in cross-functional teams Excellent communication and documentation skills Self-motivated with a continuous learning mindset Strong attention to quality and engineering best practices Key Performance Indicators (KPIs) Success in this role will be measured by: Delivery of production-ready AI services Platform stability and reliability Code quality and maintainability Deployment frequency and release quality Development of reusable AI accelerators Creation of shared platform components Contribution to product roadmap execution

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