Time since we first saw it
Day 28
Similar jobs usually come down between day 6 and day 70.
At Brillio-2, jobs usually come down by about day 25.
From 4,474 similar postings that came down, and 58 of Brillio-2’s. Coming down is not always a hire.
Lead AI/ML Engineer
Bangalore, Karnataka, India
Live, first seen by us 28 days ago- Pay
- Pay not listed
- Work setting
Hybrid — work setting source
Work setup in the employer’s posting: hybrid
From the employer’s posting- Employment
- Not stated
What you’ll work on
Full postingDesign, build and deploy AI agents and multi-agent systems on Azure
Build enterprise RAG solutions with Azure AI Search and vector search
Integrate AI workflows with Microsoft 365, Teams, SharePoint and Dynamics 365
Establish observability, guardrails and monitoring for production AI apps
Optimize agent and LLM applications for latency, accuracy, cost and security
From the employer’s posting
Design, build, and deploy AI agents and multi-agent systems using Azure AI services, Azure OpenAI
Implement enterprise RAG solutions utilizing Azure AI Search, vector search, hybrid search, and semantic ranking
Develop and operationalize agentic workflows for business functions, integrating AI solutions with Microsoft 365, Teams, SharePoint, Dynamics 365, Power Platform
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
What you’ll bring
All qualificationsCore experience
- Hands-on experience with Azure AI services, Azure OpenAI, and Azure AI Foundry
- Python programming for AI/ML solutions
- Expertise in agentic frameworks (Semantic Kernel, LangChain, LangGraph, AutoGen)
Preferred experience
- Experience with Azure Functions, Azure Container Apps, Azure Kubernetes Service (AKS), and Azure Storage
- Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, or a closely related discipline
- Proficiency in R and R Studio for statistical computing
- Knowledge of SAS or SPSS for advanced statistical modeling
Qualification wording
Hands-on experience with Azure AI services, Azure OpenAI, and Azure AI Foundry
Python programming for AI/ML solutions
Expertise in agentic frameworks (Semantic Kernel, LangChain, LangGraph, AutoGen)
Experience with Azure Functions, Azure Container Apps, Azure Kubernetes Service (AKS), and Azure Storage
Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, or a closely related discipline
Proficiency in R and R Studio for statistical computing
Knowledge of SAS or SPSS for advanced statistical modeling
Education & alternatives
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)
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Oct 8, 202628 days ago
- Recorded sightings
- 70
- Last seen by us
- Nov 5, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Brillio-2 is hiring
46 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- ML Engineer hiring is steady
- Takes jobs down at a usual pace
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- R
- SAS
- AWS
- Azure
- Kubernetes
- Keras
- PyTorch
- TensorFlow
Where the posting names them
- 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)
- 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
- 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
- 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) Employment type
- 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)
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.
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.
- 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.
Required Skills: - Hands-on experience with Azure AI services, Azure OpenAI, and Azure AI Foundry - Expertise in agentic frameworks (Semantic Kernel, LangChain, LangGraph, AutoGen)
- Model evaluation and observability tools (Evidently AI, Great Expectations) - AI security and governance on Azure Preferred Skills:
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
- Python programming for AI/ML solutions - ML frameworks (TensorFlow, PyTorch, Sci-Kit Learn, Keras) - AI workflow orchestration tools (KubeFlow, BentoML)
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Demand for ML Engineer roles
New ML Engineer postings at the employers we follow are up 12% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
US government figures for computer and information research scientists
- Median yearly pay, May 2025
- $140,300
- Expected change, 2025 to 2035
- 21.8% more jobsagainst 3.5% for all jobs
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
Job description
Lead AI/ML Engineer
Job requirements
- 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.
- 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
- 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
- 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)
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:
Required Skills:
Preferred Skills:
Desired Qualifications:
Employment type
Employee
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
Bangalore, Karnataka, India
- 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.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.