Reads like an AI Engineer role: building products on existing AI models.
Gurugram, Haryana, India
Open 3 months, first seen by us 93 days agoWork setup in the employer’s posting: HybridFrom the employer’s posting
Employment type in the employer’s posting: Full timeFrom the employer’s posting
Lead the design of enterprise-grade GenAI and agentic architectures (single-agent, multi-agent, tool-driven systems).
Drive scalability, reliability, cost optimisation, and performance across GenAI platforms.
Define MLOps / LLMOps pipelines including CI/CD, monitoring, observability, and evaluation.
Architecture & Solution Leadership Lead the design of enterprise-grade GenAI and agentic architectures (single-agent, multi-agent, tool-driven systems). Define reference architectures, reusable frameworks, and best practices for LLM applications across the organisation.
Data ingestion → chunking → embeddings → vector search → orchestration → response synthesis. Drive scalability, reliability, cost optimisation, and performance across GenAI platforms. Agentic & LLM Engineering (Hands-on + Oversight)
Architect production-grade APIs and services (FastAPI/Flask/enterprise microservices) for LLM solutions. Define MLOps / LLMOps pipelines including CI/CD, monitoring, observability, and evaluation. Partner with Data Engineering teams to ensure:
15+ years of total experience in Data Engineering / Data Science / AI
Strong Python/Pyspark engineering expertise (production-grade development) with proven API integration experience
Prior experience in one or more:
Experience with enterprise GenAI deployments (security, privacy, governance)
Open 3 monthsWe first saw this posting 93 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 93
Up longer than most. Similar jobs usually come down between day 4 and day 77.
Well past EXL Service’s usual: its jobs come down by about day 21.
From 51 similar postings that came down, and 281 of EXL Service’s. Coming down is not always a hire.
211 open jobs
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Core Engineering - Strong Python/Pyspark engineering expertise (production-grade development) with proven API integration experience - Deep data analysis experience and handling large volume of data
- Cloud platforms (Azure/AWS/GCP) - SQL - Containers, CI/CD, monitoring
- Good exposure to: - Cloud platforms (Azure/AWS/GCP) - SQL
- Deep data analysis experience and handling large volume of data - Fabric/Azure Databricks/Snowflake data engineering integration skills - Good exposure to:
- Experience with enterprise GenAI deployments (security, privacy, governance) - Experience with Azure ecosystem (Azure OpenAI, AI Search, Fabric, etc.) - Exposure to industry use cases (Insurance, BFSI, Healthcare, Retail, etc.)
Platform & Engineering Excellence - Architect production-grade APIs and services (FastAPI/Flask/enterprise microservices) for LLM solutions. - Define MLOps / LLMOps pipelines including CI/CD, monitoring, observability, and evaluation.
Complete your application on fa-ewjt-saasfaprod1.fa.ocs.oraclecloud.com. The employer’s form will show what is required.
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Yes. We’ve followed one other Principal Architect AI Data Engineer job there since August 2026. It came down after 19 days.
New AI Engineer postings at the employers we follow are up 134% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 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.
We file this job under AI Engineer, by the work the posting describes.
AI engineers build products on top of AI models that already exist, most often large language models: they connect a model to a company's data and tools and ship the assistants, agents and search features people use.
Postings ask for strong Python or TypeScript, experience with model APIs, retrieval and agent frameworks, and ways to test whether the model's answers are good enough.
An ML engineer trains and serves models; an AI engineer usually starts from a model someone else trained and builds the product around it, though titles often mix the two.
Key Responsibilities
Architecture & Solution Leadership
Agentic & LLM Engineering (Hands-on + Oversight)
Platform & Engineering Excellence
Organisation-Level Responsibilities (Critical)
Capability Building & CoE Development
Strategic & Stakeholder Leadership
Governance, Risk & Compliance
Mentorship & Team Leadership
Experience & Must-Have Skills
Experience
LLM / GenAI & Agentic Engineering
Core Engineering
Data / AI Foundations (Mandatory)
Prior experience in one or more:
Analytics engineering / data products
Good-to-Have / Preferred
Key Responsibilities
Architecture & Solution Leadership
Agentic & LLM Engineering (Hands-on + Oversight)
Platform & Engineering Excellence
Organisation-Level Responsibilities (Critical)
Capability Building & CoE Development
Strategic & Stakeholder Leadership
Governance, Risk & Compliance
Mentorship & Team Leadership
Experience & Must-Have Skills
Experience
LLM / GenAI & Agentic Engineering
Core Engineering
Data / AI Foundations (Mandatory)
Prior experience in one or more:
Analytics engineering / data products
Good-to-Have / Preferred
Key Responsibilities
Architecture & Solution Leadership
Agentic & LLM Engineering (Hands-on + Oversight)
Platform & Engineering Excellence
Organisation-Level Responsibilities (Critical)
Capability Building & CoE Development
Strategic & Stakeholder Leadership
Governance, Risk & Compliance
Mentorship & Team Leadership
Experience & Must-Have Skills
Experience
LLM / GenAI & Agentic Engineering
Core Engineering
Data / AI Foundations (Mandatory)
Prior experience in one or more:
Analytics engineering / data products
Good-to-Have / Preferred
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Gurugram, Haryana, India
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