AI/ML Engineer

Infosys Pontoon•New York, NY

1d•Hybrid

About The Position

Design and develop scalable AI-powered data platforms and agentic AI solutions that enable autonomous decision-making, intelligent workflow orchestration, and business process automation. Build and maintain data engineering pipelines using Python, Spark, Databricks, Snowflake, SQL, and cloud-native technologies to support AI/ML, GenAI, and analytics workloads. Architect and implement multi-agent AI systems with goal decomposition, task planning, reasoning, memory management, self-reflection, tool utilization, and autonomous execution capabilities. Develop and optimize Retrieval-Augmented Generation (RAG) solutions, including document ingestion, chunking, embedding generation, vector database integration, retrieval optimization, and response grounding. Integrate AI agents with enterprise systems, APIs, databases, knowledge repositories, CI/CD pipelines, and event-driven architectures to create end-to-end intelligent automation frameworks. Design and implement data governance, security, guardrails, monitoring, and compliance controls to support responsible AI adoption and protect enterprise data assets. Build reusable AI engineering components using frameworks such as LangChain, LangGraph, Semantic Kernel, ClientP-based architectures, and agent orchestration platforms. Evaluate and improve AI system performance through prompt engineering, agent testing frameworks, model benchmarking, retrieval accuracy analysis, latency optimization, and continuous feedback loops. Collaborate with architects, data scientists, application teams, and business stakeholders to translate business requirements into scalable AI-driven data solutions and production-ready platforms. Provide technical leadership and mentorship by promoting AI engineering best practices, conducting architecture reviews, developing reusable accelerators, and enabling teams to use AI-assisted software development and agentic SDLC methodologies.

Requirements

More than 10 years of experience.
Experience with GenAI, AI/ML, RAG, LangChain, Python, Spark, and Snowflake.
Skills in Python, PySpark, SQL, Databricks, Snowflake, GenAI, Agentic AI, ClientP Architecture, RAG, LangChain, LangGraph, and Semantic Kernel.

Nice To Haves

Azure

Responsibilities

Design and develop scalable AI-powered data platforms and agentic AI solutions for autonomous decision-making, workflow orchestration, and business process automation.
Build and maintain data engineering pipelines using Python, Spark, Databricks, Snowflake, SQL, and cloud-native technologies.
Architect and implement multi-agent AI systems with planning, reasoning, memory, tool-use, and autonomous execution capabilities.
Develop and optimize RAG solutions, including document ingestion, chunking, embeddings, vector database integration, retrieval, and response grounding.
Integrate AI agents with enterprise systems, APIs, databases, knowledge repositories, CI/CD pipelines, and event-driven architectures.
Implement data governance, security, guardrails, monitoring, and compliance controls for responsible AI and enterprise data protection.
Build reusable AI engineering components using modern frameworks and agent orchestration platforms.
Evaluate and improve AI system performance through prompt engineering, testing, benchmarking, retrieval analysis, latency optimization, and feedback loops.
Collaborate with technical teams and business stakeholders to turn requirements into scalable AI-driven data solutions and production-ready platforms.
Provide technical leadership and mentorship, conduct architecture reviews, develop reusable accelerators, and enable AI-assisted software development and agentic SDLC practices.
Code, test, and deploy solutions.