AI/ML Developer

Job Overview:

• We are in search of skilled AI ML Engineers with the ability to develop and implement enterprise-level Machine Learning Generative AI and Agentic AI solutions.
• The perfect candidate will possess a solid foundation in Python and Machine Learning, complemented by hands-on experience with AWS AI ML services, Retrieval Augmented Generation (RAG), LLM integration, and agentic workflows.
• You should be adept at guiding solutions from the stages of experimentation and model development through to deployment, evaluation, monitoring, and operational management.
• This role is focused on practical engineering for professionals who have successfully built real ML Generative AI solutions, rather than merely experimenting with LLM APIs.

Primary Responsibilities:

• Design and implement comprehensive ML and Generative AI pipelines on AWS utilizing Amazon SageMaker and Amazon Bedrock.
• Create intelligent LLM-driven agents and Agentic AI workflows using LangGraph and/or LangChain.
• Architect production-ready RAG solutions that encompass document ingestion, chunking, embeddings, metadata, vector indexing, retrieval, and response generation.
• Develop and productionize ML models for various use cases, including forecasting, recommendations, predictions, and customer analytics.
• Incorporate foundation models and LLM APIs, such as Amazon Bedrock and OpenAI, into scalable enterprise applications.
• Design robust workflows for prompting, context management, and tool calling orchestration for LLM applications.
• Implement LLM evaluation strategies, grounding techniques, and responsible AI safeguards to mitigate hallucination.
• Construct semantic and hybrid retrieval solutions utilizing vector search technologies like FAISS, Pinecone, and OpenSearch.
• Utilize MLOps and LLMOps principles for model and application deployment, versioning, evaluation, monitoring, and lifecycle management.
• Develop scalable Python-based APIs and services to enhance AI ML capabilities for downstream applications.
• Collaborate with data engineers, architects, product teams, and cloud platform engineers to transition AI solutions from prototypes to full production.
• The focus on RAG construction, evaluation, production agents, vector indexing, and LangGraph/LangChain aligns closely with current internal AI engineering requirements at Infosys.

Technical Qualifications:

• Essential Skills
• Candidates must demonstrate substantial hands-on experience in several of the following:
• Programming in ML
• Proficient in Python
• Scikit-learn
• TensorFlow and/or PyTorch
• Development and deployment of Machine Learning models
• Knowledge of ML pipelines and MLOps principles
• Generative AI and Agentic AI
• Development of Generative AI LLM applications
• Experience with LangGraph and/or LangChain
• Understanding of Agentic AI and AI Agents
• Expertise in Retrieval Augmented Generation (RAG)
• Proficiency in Prompt Engineering
• Embeddings and semantic retrieval
• LLM evaluation and grounding techniques
• Tool function calling and agent orchestration
• AWS familiarity
• Experience with Amazon Bedrock
• Experience with Amazon SageMaker
• Proficient in deploying AI ML workloads in AWS environments
• LLM Integration expertise
• Integration of Amazon Bedrock models or OpenAI APIs
• Foundation model integration
• API-driven Generative AI applications
• Knowledge of Vector Search Databases
• FAISS
• Pinecone
• OpenSearch
• Or similar vector database retrieval technologies
• Recent hiring documentation at Infosys emphasizes LangGraph, LangChain, RAG, Pinecone, FAISS-type vector stores, prompt engineering, evaluation, and production AI engineering.

Additional Information:

• Experience: 5 to 15 Years
• Locations: Bangalore, Chennai, Pune, Hyderabad, Trivandrum
• Employment Type: Full-time

Preferred Skills:

Technology->AI-AI Engineering->AI/ML Solution Architecture and Design->traditional AI ML