AI/ML Engineer- Contract and Onsite

World Wide Technology

Bengaluru

Sur place

INR 1 200 000 - 1 800 000

Plein temps

Il y a 5 jours
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Résumé du poste

WorldWide Technology seeks an AI/ML Engineer for onsite, long- term contract in Bengaluru. You will design, build, and deploy AI-powered applications leveraging GenAI, LLMs, RAG, and agentic workflows. You’ll implement prompt engineering, evaluation, and governance, collaborating with data and product teams.

The role requires hands-on development across the AI lifecycle, from prototyping to deployment, with emphasis on scalable APIs and enterprise integration.

Qualifications

  • 3-5 years of software engineering, machine learning, or AI engineering experience.
  • Strong proficiency in Python.
  • Experience building applications using Generative AI and LLM technologies.
  • Experience with RAG architectures and vector databases.
  • Knowledge of REST APIs and modern software development practices.
  • Familiarity with cloud platforms such as Azure or AWS.
  • Experience using Git and CI/CD practices.
  • Strong problem-solving and communication skills.

Responsabilités

  • Design, develop, and deploy AI-powered applications and services.
  • Build and optimize RAG pipelines using vector databases and enterprise knowledge sources.
  • Develop agentic workflows and AI assistants capable of reasoning, planning, and executing business tasks.
  • Implement prompt engineering, context management, and orchestration patterns to improve AI performance.
  • Integrate AI capabilities with enterprise applications, APIs, and data products.
  • Define and execute AI evaluation and testing strategies.
  • Support governance, security, privacy, and compliance requirements.

Connaissances

Python
Generative AI
LLMs
RAG architectures
REST APIs
Cloud platforms (Azure/AWS)
Git
CI/CD
Problem solving
Communication

Outils

LangChain
LangGraph
Semantic Kernel
AutoGen
CrewAI
Pinecone
ChromaDB
Weaviate
Azure OpenAI
OpenAI APIs
Anthropic Claude
Gemini

Description du poste

Worldwide Technology (WWT), a 36-year-old global technology solutions provider specializing in systems integration, Infra-Cloud security, application development, AI Services, and supply chain solutions. With a workforce of 10,000+ employees and strategic partnerships with leading OEMs such as Cisco, Dell EMC, Microsoft, and NVIDIA, WWT delivers cutting-edge infrastructure, cloud, security, and custom application services to clients across 35 countries. Our Advanced Technology Centers (ATCs)lab setup environments spanning over one million square feet of worldclass integration and distribution space enable us to deliver unmatched value and innovation at scale. Recognized as one of the Best Places to Work by Glassdoor and Fortune for 14 consecutive years, WWT is also ranked #6 on Indias Great Place to Work list for 2025.

WorldWide Technology Holding Co, LLC. (WWT) currently has an exciting opportunity available for the role of AI/ML Engineer - Onsite-long Term Contract Opportunity.

Role: AI/ML Engineer

Location: Bangalore

Contract Duration: 6 months +

Job Description

We are seeking a motivated AI Engineer to design, develop, and deploy AI-powered applications that leverage Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), agentic workflows, and machine learning techniques.

This role requires hands‑on technical execution across the AI development lifecycle, from prototyping and prompt engineering through deployment, evaluation, monitoring, and continuous improvement.

Key Responsibilities
AI Solution Development
  • Design, develop, and deploy AI-powered applications and services.
  • Build and optimize RAG pipelines using vector databases and enterprise knowledge sources.
  • Develop agentic workflows and AI assistants capable of reasoning, planning, and executing business tasks.
  • Implement prompt engineering, context management, and orchestration patterns to improve AI performance.
  • Integrate AI capabilities with enterprise applications, APIs, and data products.
LLM & GenAI Engineering
  • Work with commercial and open‑source LLMs to build intelligent solutions.
  • Evaluate and improve model performance, accuracy, grounding, and response quality.
  • Implement guardrails, citation frameworks, and validation mechanisms to improve trustworthiness.
  • Support experimentation with agent frameworks, tool calling, workflow orchestration, and emerging AI technologies.
Data & Platform Integration
  • Collaborate with data engineering teams to prepare and consume structured and unstructured data.
  • Implement vector search, embeddings, semantic retrieval, and knowledge management solutions.
  • Integrate AI solutions with cloud‑native services and enterprise platforms.
  • Build scalable APIs and services to serve AI capabilities to users and applications.
Testing & Evaluation
  • Define and execute AI evaluation and testing strategies.
  • Develop test datasets, benchmarks, and evaluation metrics for AI systems.
  • Identify and mitigate hallucinations, grounding issues, and response quality concerns.
  • Monitor solution performance and recommend enhancements.
AI Governance & Compliance
  • Support responsible AI, security, privacy, and compliance requirements.
  • Maintain documentation required for AI governance reviews and approvals.
  • Contribute to AI Registry submissions and supporting documentation where applicable.
  • Partner with product and engineering teams to ensure AI solutions meet enterprise standards.
Required Qualifications
  • 3-5 years of software engineering, machine learning, or AI engineering experience.
  • Strong proficiency in Python.
  • Experience building applications using Generative AI and LLM technologies.
  • Experience with RAG architectures and vector databases.
  • Knowledge of REST APIs and modern software development practices.
  • Familiarity with cloud platforms such as Azure or AWS.
  • Experience using Git and CI/CD practices.
  • Strong problem-solving and communication skills.
Preferred Qualifications
  • Experience with LangChain, LangGraph, Semantic Kernel, AutoGen, CrewAI, or similar frameworks.
  • Familiarity with Azure OpenAI, OpenAI APIs, Anthropic Claude, Gemini, or open‑source LLMs.
  • Experience with embeddings, semantic search, and vector databases such as Pinecone, ChromaDB, Weaviate, or Azure AI Search.
  • Exposure to MLOps or LLMOps practices.
  • Experience within pharmaceutical, healthcare, or regulated environments.
  • Familiarity with AI evaluation frameworks such as RAGAS, DeepEval, or LLM-as-a-Judge approaches.
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