Sr Specialist AI Engineer
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Before you apply
LocationIndia - Bangalore - Karnataka
Work modeon-site
Typefull-time
SenioritySenior
Experience5–8 yrs
DepartmentAI Engineering
Company size5,001–10,000 people
PostedSep 23, 2026 · 1mo ago
Verified live5d ago
At a glanceSummarised by Seekless from the posting.
Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Engineering, Information Technology, or a related field.
5-8 years of software engineering experience, including hands-on experience building AI-powered applications.
Strong proficiency in Python and modern software engineering practices.
Hands-on experience with LLMs such as GPT, Claude, Gemini, Llama, or similar foundation models.
Experience with LangGraph, LangChain, AutoGen, CrewAI, Semantic Kernel, LlamaIndex, or similar orchestration frameworks.
Strong understanding of Agentic AI architectures, tool calling, memory systems, reasoning frameworks, and workflow automation.
Experience building RAG applications using vector databases and semantic search technologies.
Hands-on experience with AI-assisted development tools such as GitHub Copilot, Claude Code, Cursor, or similar platforms.
Excellent communication and stakeholder management skills.
Experience in Financial Services, Capital Markets, or FinTech domains.
Experience with DeepEval, Ragas, LangSmith or similar evaluation frameworks.
Exposure to LLMOps, MLOps, Responsible AI, and AI Governance practices.
Experience with Knowledge Graphs, Graph Databases, and Enterprise Search platforms.
Skills
Python
GPT
Claude
Gemini
Llama
LangGraph
LangChain
AutoGen
CrewAI
Semantic Kernel
LlamaIndex
vector databases
semantic search
GitHub Copilot
Claude Code
Cursor
DeepEval
Ragas
LangSmith
Knowledge Graphs
Graph Databases
Enterprise Search
About the role
As a Sr Specialist - AI Engineering reporting to the Head of Market Data and AI Enablement, you will lead the design, development, and deployment of next-generation AI solutions leveraging Large Language Models (LLMs), Agentic AI frameworks, Retrieval-Augmented Generation (RAG), and intelligent automation. You will build enterprise-grade AI platforms, autonomous agents, evaluation frameworks, and AI-powered workflows that drive measurable business outcomes and engineering productivity across Nasdaq.
Working closely with global teams and stakeholders, you will architect scalable, secure, and production-ready AI systems while establishing AI engineering best practices, governance standards, and operational excellence.
You will thrive in this role if you are passionate about AI innovation, enjoy solving complex business challenges, and can successfully bring cutting-edge AI capabilities into enterprise production environments.
Roles & responsibilities :
•
Design, develop, deploy, and support enterprise-grade Agentic AI solutions, intelligent assistants, copilots, and workflow automation platforms.
•
Build and maintain Retrieval-Augmented Generation (RAG) systems using vector databases, embeddings, enterprise content sources, and knowledge repositories.
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Develop multi-agent systems that leverage planning, reasoning, memory, and tool orchestration capabilities.
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Create evaluation frameworks to measure answer relevancy, faithfulness, grounding, latency, safety, and overall business impact.
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Partner with business and technology stakeholders to translate requirements into scalable AI solutions.
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Implement AI observability, monitoring, governance, security controls, and operational best practices.
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Integrate AI systems with enterprise applications, APIs, databases, and cloud platforms.
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Drive AI-enabled automation initiatives to improve productivity, software quality, and operational efficiency.
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Mentor engineers and promote AI engineering standards, architecture patterns, and best practices.
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Evaluate emerging AI technologies, frameworks, and models and drive adoption where appropriate.
What we expect :
•
Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Engineering, Information Technology, or a related field.
•
5-8 years of software engineering experience, including hands-on experience building AI-powered applications.
•
Strong proficiency in Python and modern software engineering practices.
•
Hands-on experience with LLMs such as GPT, Claude, Gemini, Llama, or similar foundation models.
•
Experience with LangGraph, LangChain, AutoGen, CrewAI, Semantic Kernel, LlamaIndex, or similar orchestration frameworks.
•
Strong understanding of Agentic AI architectures, tool calling, memory systems, reasoning frameworks, and workflow automation.
•
Experience building RAG applications using vector databases and semantic search technologies.
•
Hands-on experience with AI-assisted development tools such as GitHub Copilot, Claude Code, Cursor, or similar platforms.
•
Excellent communication and stakeholder management skills.
Nice to have
Good to Have :
•
•
Experience in Financial Services, Capital Markets, or FinTech domains.
•
Experience with DeepEval, Ragas, LangSmith or similar evaluation frameworks.
•
Exposure to LLMOps, MLOps, Responsible AI, and AI Governance practices.
•
Experience with Knowledge Graphs, Graph Databases, and Enterprise Search platforms.
Does it sound like you? What happens now?
As the selection process is ongoing, please submit your application in English as soon as possible. We will get back to you in 2-3 weeks.