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, Computer Applications, or Science
Service Line: Cloud & Infrastructure Services
As an Infra AI Automation Programmer at Infosys, you will design, develop, and deploy AI-driven systems focused on generative content and automation. This includes leveraging deep learning, neural networks, and advanced generative models using a strong Python backend. You will work directly with clients to assess their AI readiness and create impactful AI strategies tailored to their business.
Engage with clients onsite and remotely to understand business goals and identify opportunities for applying Generative AI.
Evaluate the client’s technology infrastructure, data ecosystem, and AI maturity to determine implementation feasibility.
Conduct workshops and discovery sessions to explore Gen AI use cases in functions like customer service, product development, marketing, and content creation.
Develop client-specific Gen AI strategies, solution roadmaps, and business impact projections.
Design Gen AI architecture based on use case—selecting appropriate models (e.g., LLMs, diffusion models), ensuring system integration and scalability.
Recommend tools and APIs such as OpenAI, Azure AI, Google AI, or open-source libraries based on client needs.
Apply prompt engineering techniques to improve Gen AI output quality and alignment with business objectives.
Maintain a high standard of quality awareness and analytical thinking.
Show initiative, adaptability, and a customer-centric mindset.
Communicate effectively with both technical and business stakeholders.
Stay updated with advancements in responsible and ethical AI.
Minimum 2 years of hands-on experience in Python programming.
Proven experience working with Generative AI models and tools.
Strong background in TensorFlow, PyTorch, LangChain, and Prompt Engineering.
Experience using vector databases and retrieval-augmented generation (RAG).
Understanding of MLOps tools and principles for Gen AI deployment.
Familiarity with ethical AI and responsible AI practices.
Strong understanding of data structures, modeling, SQL/NoSQL databases.
Proficiency in Git, object-oriented and functional programming.
Solid foundation in mathematics, statistics, probability, and algorithms.
Excellent analytical, problem-solving, and communication skills.
TensorFlow (Technology → Machine Learning → TensorFlow)
Python (Technology → Machine Learning → Python)
Generative AI (Technology → Machine Learning → Generative AI)
