AI Engineer - WFO - Pune (Kharadi) - Hands on AI implementation

Role & responsibilities

JOB DESCRIPTION

AI Engineer

LOCATION

EXPERIENCE

OPEN POSITIONS

Pune (Kharadi)

6+ years

3

Role Overview

We are looking for AI Engineers to build secure, cloud-native AI applications and agentic solutions. The role combines strong software engineering with hands-on experience in the Azure AI ecosystem, retrieval-augmented generation, orchestration, and rapid experimentation.

Key Responsibilities

• Design, build, test, and deploy AI-enabled applications, assistants, and agent workflows. • Integrate large language models using Azure OpenAI Service and build retrieval-augmented generation solutions.
• Implement enterprise search and retrieval using Azure AI Search and suitable vector databases. • Build orchestration with agent frameworks such as LangChain, Semantic Kernel, AutoGen, or custom approaches.
• Expose capabilities through secure APIs and microservices and integrate with enterprise systems. • Use Azure Machine Learning or suitable platform services for deployment, evaluation, monitoring, and lifecycle management.
• Prototype rapidly, evaluate results, improve prompts and retrieval, and convert experiments into maintainable solutions.
• Apply responsible AI, security, privacy, observability, and engineering-quality practices.

Required Skills and Experience

• 6 to 8+ years of software development experience using Python, C#, or Node.js. • Hands-on experience with APIs, microservices, and cloud-native architecture.
• Experience building AI agents or orchestration frameworks.
• Knowledge of retrieval-augmented generation, embeddings, vector search, and vector databases. • Practical experience integrating generative AI models into production-oriented applications. • Strong problem-solving skills with the ability to experiment, learn, and iterate quickly.

Preferred Skills

• Experience with Azure OpenAI Service, Azure AI Search, Azure Machine Learning, Azure Bot Service, or Logic Apps.
• Experience with Azure Cosmos DB vector search, Pinecone, Weaviate, or FAISS. • Experience evaluating model quality, grounding, safety, latency, and cost.

Expected Outcomes

• Deliver useful, grounded, secure AI capabilities that solve clear business problems. • Establish reusable patterns for agent orchestration, retrieval, deployment, and monitoring.

Candidate Profile

Job Description | Confidential recruitment document Page 1

The ideal candidate is collaborative, accountable, quality-focused, comfortable working in a globally distributed environment, and able to communicate clearly with both technical and business stakeholders.

Note: This job description has been structured from the supplied role requirements. Final screening criteria, grade, compensation, work arrangement, and employment terms should be confirmed by the hiring organization.

Job Description | Confidential recruitment document Page 2