Job Title: Infra AI Automation Programmer
Job ID/Reference Code: INFSYS-EXTERNAL-216034
Location: Bangalore, India
Experience Required: 2–3 Years
Educational Requirements:
Bachelor’s or Master’s Degree in Engineering, Technology, Science, Computer Applications
Service Line: Cloud & Infrastructure Services
As an Infra AI Automation Programmer at Infosys, you will be responsible for designing, developing, and deploying AI-driven systems focused on automation and content generation. This role demands expertise in Python, Gen AI technologies, and modern AI/ML frameworks.
Meet with clients (onsite and remote) to understand business objectives and explore use cases for Generative AI.
Assess clients’ current technology stack and data infrastructure to evaluate AI readiness.
Conduct discovery workshops to identify and design Gen AI applications across departments like customer service, marketing, product development, and content creation.
Develop custom Generative AI strategies and roadmaps, outlining specific use cases and expected outcomes.
Architect scalable Gen AI solutions using appropriate models (e.g., LLMs, diffusion models) and integrate them with existing systems.
Recommend suitable Gen AI platforms, APIs, and tools such as OpenAI, Azure AI, Google AI, or open-source frameworks.
Apply prompt engineering techniques to optimize Gen AI model outputs for client-specific needs.
Provide documentation, support, and guidance on best practices to clients and internal teams.
Demonstrate high analytical thinking, customer orientation, and quality awareness.
Show flexibility, ownership, and initiative in handling evolving AI requirements.
Communicate effectively with both technical and non-technical stakeholders.
Minimum 2 years of hands-on programming experience in Python.
Experience working with Generative AI models and techniques.
Practical knowledge of frameworks like TensorFlow, PyTorch, LangChain, and Prompt Engineering.
Familiarity with vector databases and retrieval-augmented generation (RAG) methods.
Understanding of MLOps tools for Gen AI model deployment and lifecycle management.
Awareness of ethical AI practices and responsible AI governance.
Strong skills in data structures, SQL/NoSQL databases, and data modeling.
Proficiency in Git, object-oriented, and functional programming principles.
Solid foundation in algorithms, probability, and statistics.
Strong problem-solving and communication abilities.
TensorFlow – Machine Learning
Python – Machine Learning
Generative AI – Machine Learning
