Artificial Intelligence Engineer

We are looking for AI/ML Engineer

Experience: 5 years

Location: Bangalore

Work Mode: On-site

Job Type: Contract

Key responsibilities

• Agentic systems engineering: Design and implement single- and multi-agent workflows with tool-use, planning, memory, and reflection across Azure AI services; build robust RAG and tool orchestration patterns for enterprise workloads.
• MCP servers: Implement and operate MCP servers to provide structured tools and context to agents; define schemas, capabilities, and secure connectivity to Azure resources and DevOps systems.
• Azure platform implementation: Develop solutions using Azure AI Foundry, Azure AI Agent Service, Azure OpenAI, Azure Machine Learning, Azure Kubernetes Service, and Azure Functions; integrate with Azure Event Grid, Service Bus, and Key Vault.
• DevOps and LLMOps: Establish CI/CD for agents and MCP servers using Azure DevOps and GitHub Actions; implement evaluation pipelines, prompt/version management, telemetry, and rollback strategies.
• Data and RAG: Build performant RAG pipelines with Azure Cognitive Search or vector databases; define chunking, embedding strategies, and grounding for domain-specific corpora on Azure storage and data services.
• Security, governance, and compliance: Implement authentication/authorization, secrets management, content safety, auditability, and policy guardrails aligned to enterprise and regulatory requirements.
• Observability and FinOps: Instrument tracing, metrics, and cost controls for tokens, calls, and infra; optimize latency, throughput, and spend across agents, MCP servers, and Azure components.
• Collaboration and solutioning: Partner with product, security, and platform teams to translate use cases into reference architectures, estimations, and production rollouts; contribute to reusable blueprints and best practices.

Must-have qualifications

• 5+ years in software/ML engineering with at least 2 years building LLM/agent-based systems; strong Python engineering skills and API design experience.
• Demonstrated experience building agentic workflows using frameworks such as LangGraph, LangChain agents, Semantic Kernel, CrewAI, or custom planners; hands-on with tool-use and memory.
• Proven deployment of MCP servers or equivalent tool-bridge services that expose enterprise capabilities to agents; understanding of context contracts and tool permissioning models.
• Azure expertise: Azure AI Foundry, Azure AI Agent Service, Azure OpenAI, Azure ML, Azure DevOps, AKS/Containers, Functions/Logic Apps, and Key Vault.
• RAG proficiency: embeddings, vector stores, retrieval tuning, evaluation, and grounding using Azure Cognitive Search or compatible vector databases.
• DevOps/LLMOps: CI/CD for models/agents, prompt/version control, telemetry, and evaluation harnesses in Azure DevOps/GitHub.
• Security and compliance: OAuth/Entra ID integration, secret rotation, data loss prevention, content safety, audit logging, and policy enforcement for agent actions.

Nice-to-have qualifications

• Experience with Microsoft Copilot Studio and plugin/tool creation; integration with M365, Dynamics, and Power Platform.
• Background with Databricks/Spark for feature and data pipelines; familiarity with vector databases and embedding model selection.
• Knowledge of governance for agentic platforms: intake workflows, approval processes, catalogs/registries for tools and agents.
• Experience exposing Azure DevOps/Git, Work Items, and CI/CD as MCP tools to enable development workflows for agents.

Core technical skills

• Languages and frameworks: Python, TypeScript; FastAPI/Flask for services; experience with LangGraph/LangChain/Semantic Kernel for orchestration.
• Azure AI and data: Azure AI Foundry, Azure AI Agent Service, Azure OpenAI, Azure ML, Azure Cognitive Search, Azure Storage, Event Grid, Service Bus, Key Vault.
• Infra and DevOps: Azure DevOps, GitHub Actions, AKS/Container Apps, IaC (Bicep/Terraform), monitoring (Application Insights, Log Analytics).
• MCP and integrations: MCP servers and clients; secure tool adapters to enterprise systems (DevOps, databases, SaaS/line-of-business apps).

Education and certifications

• Bachelors/Masters in CS/EE or related field; Microsoft certifications such as Azure AI Engineer Associate or Azure Solutions Architect are a plus.

Interested candidates please share your resume to