Consultant ( AI Engineer)

6 days ago

Gurgaon, Haryana, India KPMG Global Services Full time

Roles & responsibilities 

Model Development & Solution Architecture



•Design, build, and optimize machine learning, GenAI, and statistical models to solve complex cross‑domain business challenges.

•Develop reproducible, scalable workflows using modern MLOps practices; conduct rigorous model evaluation and continuous improvement for accuracy, reliability, and fairness.

•Architect end‑to‑end AI systems including data pipelines, vector databases, orchestration layers, and deployment frameworks.

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GenAI, RAG & Agentic Systems



•Explore and implement advanced LLM techniques, including embeddings, retrieval‑augmented generation (RAG), agentic workflows, tool use, memory, and multimodal reasoning.

•Build production‑grade GenAI applications using LangChain, LangGraph, and ecosystem tools for orchestration, evaluation, and deployment.

•Experiment with foundation models across open‑source and commercial platforms to identify best‑fit models for business use cases.

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API & Integration Development



•Develop and operationalize scalable APIs—preferably with FastAPI (Python)—to integrate ML/GenAI components with enterprise systems, SaaS products, and data platforms.

•Collaborate on deployment patterns including microservices, serverless, and containerized workloads (Docker/Kubernetes).

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Cloud Platforms & Infrastructure



•Architect and deploy AI solutions on Azure, Google Cloud Platform (GCP), or AWS, leveraging managed AI/ML services (Azure ML, Vertex AI, SageMaker), vector search, and serverless compute.

•Ensure security, scalability, compliance, and monitoring in all cloud‑based AI deployments.

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Consulting, Problem Solving & Stakeholder Collaboration



•Partner with product teams, business stakeholders, SMEs, and engineering groups to deeply understand challenges, run discovery workshops, and shape AI strategy and roadmaps.

•Translate business requirements into scalable technical architectures, solution designs, and implementation plans.

•Communicate complex AI concepts in clear, business‑friendly language and drive adoption of AI‑powered solutions across the organization.

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