AI/ML Engineer- Contract and Onsite

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. If you are interested in this opportunity, please respond with an updated resume - "[email removed]"

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.