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Lead AI/ML Engineer – R01572495

Bangalore, Karnataka, India · Employee · Compensation not disclosed by employer

Category
AI & Data Engineering
Required Skills
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Experience
Lead
Openings
1
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November 28, 2026

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Lead AI/ML Engineer

Job requirements

    Experience Range: With at least 4 to 6 years of experience designing, building, and operationalizing enterprise-scale AI platforms, including hands-on expertise in agentic AI, LLMs, and Azure-based solutions. Key Responsibilities:
  • Design, build, and deploy AI agents and multi-agent systems using Azure AI services, Azure OpenAI, and modern agentic frameworks such as Semantic Kernel, LangChain, LangGraph, and AutoGen.
  • Develop and operationalize agentic workflows for business functions, integrating AI solutions with Microsoft 365, Teams, SharePoint, Dynamics 365, Power Platform, and enterprise APIs.
  • Implement enterprise RAG solutions utilizing Azure AI Search, vector search, hybrid search, and semantic ranking to enhance knowledge retrieval and business decision-making.
  • Build production-ready AI applications leveraging LLMs, RAG pipelines, tool/function calling, memory systems, and workflow orchestration for scalable, secure, and reliable enterprise deployment.
  • Establish observability, guardrails, responsible AI controls, evaluation, security, and monitoring for AI applications in production environments.
  • Optimize agent and LLM applications for latency, accuracy, reliability, scalability, security, and cost, applying advanced techniques and metrics.
  • Collaborate with cross-functional teams to identify AI opportunities, rapidly prototype solutions, and iterate based on user feedback.
  • Contribute to internal best practices around agent architecture, prompting, RAG, model selection, evaluation, and AI engineering standards.
  • Required Skills:
  • Hands-on experience with Azure AI services, Azure OpenAI, and Azure AI Foundry
  • Expertise in agentic frameworks (Semantic Kernel, LangChain, LangGraph, AutoGen)
  • LLM application development and prompt engineering
  • Enterprise RAG architectures and vector search technologies
  • Integration with Microsoft 365, Teams, SharePoint, Dynamics 365, Power Platform, and APIs
  • Python programming for AI/ML solutions
  • ML frameworks (TensorFlow, PyTorch, Sci-Kit Learn, Keras)
  • AI workflow orchestration tools (KubeFlow, BentoML)
  • Model evaluation and observability tools (Evidently AI, Great Expectations)
  • AI security and governance on Azure
  • Preferred Skills:
  • Experience with Azure Functions, Azure Container Apps, Azure Kubernetes Service (AKS), and Azure Storage
  • Proficiency in R and R Studio for statistical computing
  • Knowledge of SAS or SPSS for advanced statistical modeling
  • Familiarity with microservices, event-driven architectures, and enterprise integrations
  • Expertise in developing reusable agent frameworks, prompt libraries, and deployment patterns
  • Desired Qualifications:
  • Bachelor’s degree in Computer Science, Data Science, Statistics, Mathematics, or a closely related discipline
  • Certification in Machine Learning or Data Science from a recognized institution (e.g., TensorFlow Developer Certificate, AWS Certified Machine Learning Specialty, Microsoft Certified: Azure AI Engineer Associate)
  • Certification in statistical analysis tools or platforms (e.g., SAS Certified Statistical Business Analyst)

Responsibilities

• Lead end-to-end execution of projects and cross-functional deliverables for Lead AI/ML Engineer - R01572495.
• Collaborate closely with departmental peers and stakeholders to ensure seamless operational continuity.
• Monitor core performance KPIs, troubleshoot bottlenecks, and implement optimization protocols.
• Champion high quality standards, peer reviews, and comprehensive team documentation.

Candidate Skill Fit Analysis

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Required competencies and technical background for this position:

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Estimated In-Hand Salary

New Tax Regime (AY 2026–27)

Editable what-if calculation; when employer pay is not disclosed, the starting amount is an example, not a salary offer. Indicative estimate using standard assumptions for EPF, professional tax and Section 87A. Actual payroll, benefits and deductions vary by employer and individual.

₹1,200,000
Monthly In-Hand ₹--
Annual Take-Home ₹--
Standard Deduction: ₹75,000 / yr
Employee PF (EPF): ₹-- / mo
Estimated Income Tax: ₹-- / mo
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