Large Language Model Architect
Bengaluru
| Full time
| Experience: 12-14 years
Required Skill: Large Language Models (LLMs)
AI / ML Engineer
AI/ML Computational Science Team Lead/Consultant
|
Full time
|
Experience: 5-10 years
ジョブ番号 ATCI-5499208-S2010317
|
Bengaluru
|
Required Skill: Large Language Models (LLMs)
Project Role : AI / ML Engineer
Project Role Description : Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing.
Must have skills : Large Language Models (LLMs)
Good to have skills : NA
Minimum 5 year(s) of experience is required
Educational Qualification : 15 years full time education
Summary
As Senior AI Engineer, you are a critical member of the AI and Automation group focused on leading efforts in migrating Agentic AI based solutions from concept to production-level operational excellence. A key component of this will be operationalizing new tools, platforms and infrastructure as well as standing up production, development and QA environments. You will work towards building scalable, resilient, and automated solutions in both GCP (Google Cloud Platform) and Agentic platforms to ensure that models and agents deliver on organizational objectives. You will professionally engineer solutions taking into account notions of risk and FMEA (failure modes and effects analysis).
Key Accountabilities
As part of the team, you will be working as a Senior AI Engineer to operationalize key strategic ML models.
Research and operationalize and support new tools, frameworks, and platforms technology and processes necessary to scale AI Solutions.
Building, maintaining and troubleshooting Agentic custom connectors, custom actions and other associated integration work. Must Have
End-to-end responsibility for operationalizing ML Dev Ops tools and processes including installation, maintenance, documentation, best practices, training, and championing.
Responsible for creating and maintaining both production and lower environments (stage, QA, development).
Create and operationalize quality assurance processes for ML models.
Ownership of cloud security compliance.
Monitor and optimize cloud spend.
Experience in Communication protocols, e.g. MCP Must have
Optimize deployment and change control processes for models.
Minimum Qualifications
Bachelor s degree in a quantitative field (CS, engineering, statistics, math, data science).
At least 3 years professional experience as a software engineer, integration engineer, ML Engineer, AI Engineer or data scientist.
Strong python development skills.
Must have strong familiarity with the GCP / Vertex AI Platform
Experience integrating third party products such as SalesForce, ServiceNow, SAP, OneTrust, and Workday with GCP pipelines. Ideally building connectors and actions for Glean.
Experience building and utilizing APIs and End Points ideally within a GCP environment.
Background in at least one Agentic AI platform preferred with a specific preference for Glean.
Must have Background in Cloud Engineering in a GCP environment.
General background building, maintaining and supporting traditional ML Pipelines in a GCP environment is must have.
Strong understanding of orchestration frameworks such as Airflow.
Ability to mentor others and lead the team in technology and best practices.
Project Role Description : Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing.
Must have skills : Large Language Models (LLMs)
Good to have skills : NA
Minimum 5 year(s) of experience is required
Educational Qualification : 15 years full time education
Summary
As Senior AI Engineer, you are a critical member of the AI and Automation group focused on leading efforts in migrating Agentic AI based solutions from concept to production-level operational excellence. A key component of this will be operationalizing new tools, platforms and infrastructure as well as standing up production, development and QA environments. You will work towards building scalable, resilient, and automated solutions in both GCP (Google Cloud Platform) and Agentic platforms to ensure that models and agents deliver on organizational objectives. You will professionally engineer solutions taking into account notions of risk and FMEA (failure modes and effects analysis).
Key Accountabilities
As part of the team, you will be working as a Senior AI Engineer to operationalize key strategic ML models.
Research and operationalize and support new tools, frameworks, and platforms technology and processes necessary to scale AI Solutions.
Building, maintaining and troubleshooting Agentic custom connectors, custom actions and other associated integration work. Must Have
End-to-end responsibility for operationalizing ML Dev Ops tools and processes including installation, maintenance, documentation, best practices, training, and championing.
Responsible for creating and maintaining both production and lower environments (stage, QA, development).
Create and operationalize quality assurance processes for ML models.
Ownership of cloud security compliance.
Monitor and optimize cloud spend.
Experience in Communication protocols, e.g. MCP Must have
Optimize deployment and change control processes for models.
Minimum Qualifications
Bachelor s degree in a quantitative field (CS, engineering, statistics, math, data science).
At least 3 years professional experience as a software engineer, integration engineer, ML Engineer, AI Engineer or data scientist.
Strong python development skills.
Must have strong familiarity with the GCP / Vertex AI Platform
Experience integrating third party products such as SalesForce, ServiceNow, SAP, OneTrust, and Workday with GCP pipelines. Ideally building connectors and actions for Glean.
Experience building and utilizing APIs and End Points ideally within a GCP environment.
Background in at least one Agentic AI platform preferred with a specific preference for Glean.
Must have Background in Cloud Engineering in a GCP environment.
General background building, maintaining and supporting traditional ML Pipelines in a GCP environment is must have.
Strong understanding of orchestration frameworks such as Airflow.
Ability to mentor others and lead the team in technology and best practices.
15 years full time education
Bengaluru
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