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Job Description
Job Overview:
- We are on the lookout for a skilled Generative AI Engineer who possesses in-depth knowledge of Agentic AI, AI Agent Frameworks, RAG (Retrieval Augmented Generation), MCP (Model Context Protocol), and the development of LLM (Large Language Model) applications.
- The successful candidate will be responsible for the design, development, and deployment of enterprise-level GenAI solutions, utilizing advanced agent orchestration frameworks, vector databases, and cloud technologies.
Core Responsibilities:
- A typical day as part of the Infosys delivery team involves
- Engaging with clients to ensure quality assurance, resolve issues, and maintain high levels of customer satisfaction.
- Understanding requirements, creating and reviewing designs, validating architecture, and ensuring the delivery of superior service offerings to clients within the technology sector.
- Participating in project estimation, providing insights for solution delivery, conducting technical risk assessments, and executing code and unit test plan reviews.
- Leading and mentoring teams to produce optimized, high-quality code deliverables, while continuously managing knowledge and adhering to organizational standards and processes.
- Playing a pivotal role in constructing efficient programs and systems; if you believe you can contribute to guiding our clients through their digital transformation journey, this role is ideal for you.
- If you are ready to assist our clients in navigating their next steps in digital transformation, this opportunity is for you.
Technical Qualifications:
- 5 to 9 years of experience in software development.
- Proven hands-on expertise in Generative AI.
- Familiarity with Agentic AI architectures.
- Proficiency in AI Agent Frameworks including
- LangGraph
- AutoGen
- CrewAI
- Semantic Kernel
- LangChain Agents
- Extensive experience in RAG (Retrieval Augmented Generation).
- Practical knowledge of MCP (Model Context Protocol).
- Experience with LLMs such as OpenAI, Azure OpenAI, Claude, Gemini, and Llama.
- Proficiency in Python development.
- Expertise in Prompt Engineering and AI application development.
- Experience with Vector Databases like Pinecone, ChromaDB, Weaviate, FAISS, and Azure AI Search.
- Roles and Responsibilities include:
- Designing and developing enterprise-grade Agentic AI applications.
- Creating multi-agent workflows using contemporary agent frameworks.
- Implementing RAG pipelines by leveraging vector databases and enterprise knowledge bases.
- Integrating AI agents with enterprise applications via MCP.
- Optimizing prompts, retrieval strategies, and agent orchestration workflows.
- Developing APIs and backend services that support GenAI solutions.
- Deploying, monitoring, and refining LLM-driven applications.
- Collaborating with business and engineering teams to identify AI use cases and strategize solutions.
- Ensuring scalability, security, and adherence to responsible AI practices.
Additional Responsibilities:
- Preferred Skills include
- Azure OpenAI Services
- AWS Bedrock
- Databricks Mosaic AI
- AI Observability tools such as LangSmith, PromptFlow, and Phoenix.
- Containerization technologies like Docker and Kubernetes.
- MLOps and LLMOps practices.
- GraphRAG expertise.
- Knowledge of Knowledge Graphs.