ML Engineer I

Role Description Primary Skills: Python AI/ML engineering, , Agentic Layer A2A frameworks and MCP Protocol

• Senior AI Engineers

Job Description Primary Skill Python AI/ML and cloud. Business 10X Engineering Skill Category Super Super Niche JOB POSITION 5+ years of experience in software development, with a strong focus on full-stack and cloud technologies. Hands-on experience with Agentic Layer A2A frameworks and MCP Protocol. Experience with LangChain and LangGraph for building and orchestrating LLM-powered applications and workflows. Expertise in AI/ML engineering, specifically vector embeddings, prompt engineering, and context engineering. Strong programming skills in at least two of the following: Python, Java, Go. Proficiency in deploying solutions on Azure Cloud. Experience with databases such as Azure AI Search, VectorDB, Redis, and Cosmos DB (Blob Storage and Iceberg are plus). Proven ability to design and manage Azure Functions and Azure Container Apps. Strong understanding of cloud-native architecture, scalability, and performance optimization. Design and implement AI-driven solutions that align with business objectives. Expertise in AI/ML frameworks like TensorFlow and PyTorch, Agentic frameworks like LlamaIndex, LangChain Develop AI models, systems and infrastructure, including GenAI tools (e.g. GPT, GANs) NLP tools (SpaCy, NLTK, Hugging Face), ML and DL tools. Proficiency and hands-on experience in programming languages such as Python, R, Java, or C++. Collaborating with data scientists, engineers, and business stakeholders. Guide technology selection, ensuring solutions align with business goals and compliance standards. Developing scalable AI architectures and ensuring seamless integration with existing systems. Overseeing AI model deployment, optimization, and performance monitoring. Ensuring compliance with ethical AI guidelines and data privacy regulations. Strong understanding of cloud-native architecture, scalability, and performance optimization. Strong knowledge of DevOps, MLOps, and CI/CD pipelines. Understanding of big data technologies and analytics is preferable RDBMS (Oracle., SQL server or DB2) NoSQL (Mongo/docDb) Health care domain knowledge is preferable Excellent problem-solving skills and ability to think critically. Solid understanding of software development methodologies such as Agile and Scrum. JOB RESPONSIBILITY Strategic Planning - Developing AI strategies that integrate with enterprise goals and identifying opportunities for AI adoption. Solution Architecture - Design scalable AI frameworks, ensuring seamless integration with enterprise systems. Architecture & Development: Overseeing the development of scalable, high-performing applications requires a strategic approach, regardless of the tech stack. Code Quality & Reviews: Conduct code reviews and enforce best practices for clean, maintainable code. Collaboration - Working closely with data scientists, engineers, and business stakeholders to ensure AI solutions meet organizational needs. Model Deployment & Optimization - Overseeing AI model implementation, monitoring performance, and refining algorithms for efficiency. Security & Compliance - Ensuring AI solutions adhere to ethical guidelines, data privacy regulations, and cybersecurity best practices. Integration & Deployment: Ensure seamless integration of front-end and back-end components. Continuous Improvement - Establishing feedback loops to enhance AI models and maintain system reliability. Mentorship: Guide junior developers, providing technical support and career development. Innovation & Research. QUALIFICATION Bachelor's/master s degree in computer science or equivalent.

Experience Technical Experience: Machine Learning & AI - Expertise in AI models, neural networks, and ML frameworks like TensorFlow and PyTorch. Programming Languages - Proficiency in Python, R, Java, or C++ for AI development Front-End Development: Knowledge in HTML, CSS, JavaScript, React, Angular is value added. Microservices Architecture: Ability to design and implement scalable microservices. Data Engineering - Experience with ETL processes, data lakes, and big data technologies would be added advantage. Database Management: Knowledge of SQL, NoSQL, PostgreSQL, MongoDB. Cloud Computing - Familiarity with AWS, Azure, or Google Cloud for scalable AI solution. DevOps & MLOps - Knowledge of CI/CD pipelines, containerization (Docker, Kubernetes), and model deployment. Security & Compliance - Understanding of ethical AI, data privacy regulations, and cybersecurity best practice

Leadership & Management Experience Code Reviews & Best Practices: Enforcing coding standards and best practices. Agile & Scrum Methodologies Security & Performance Optimization. Unit Test frameworks.

Skills And Competencies Back-End: Python, R, Java,. Front-End: HTML, CSS, JavaScript, React, Angular. Cloud & DevOps: AWS, Azure, CI/CD pipelines, Docker, Kubernetes. Database Management: SQL, NoSQL, PostgreSQL, MongoDB. Repo & Build tools: Bitbucket, Git & Maven Agile Project Management:- Jira

Skills python,ai/ml,cloud,agentic layer a2a frameworks,mcp protocol,