Lead I - ML Engineering

Primary Skills: Python AI/ML engineering, , Agentic Layer A2A frameworks and MCP Protocol -Senior AI Engineers 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