18 hours ago
Bengaluru, IndiaSenior
Responsibilities
- Design, develop, deploy, and support enterprise-grade Agentic AI solutions, intelligent assistants, copilots, and workflow automation platforms.
- Build and maintain Retrieval-Augmented Generation systems using vector databases, embeddings, enterprise content sources, and knowledge repositories.
- Develop multi-agent systems with planning, reasoning, memory, and tool orchestration capabilities.
- Create evaluation frameworks measuring relevancy, faithfulness, grounding, latency, safety, and business impact.
- Translate stakeholder requirements into scalable AI solutions and integrate systems with enterprise applications, APIs, databases, and cloud platforms.
- Implement AI observability, monitoring, governance, security controls, and operational best practices.
- Drive AI-enabled automation initiatives and evaluate emerging AI technologies, frameworks, and models.
- Mentor engineers and promote AI engineering standards, architecture patterns, and best practices.
Requirements
- 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, and Cursor.
- Excellent communication and stakeholder management skills.
- Preferred: experience in Financial Services, Capital Markets, or FinTech.
- Preferred: experience with DeepEval, Ragas, LangSmith, LLMOps, MLOps, Responsible AI, AI Governance, knowledge graphs, graph databases, or enterprise search platforms.
Benefits
- Annual monetary bonus.
- Opportunity to become a Nasdaq shareholder and participate in the Nasdaq Employee Stock Purchase Program with a discount.
- Health Insurance Program.
- Flexible working schedule and hybrid way of work in a hybrid-first environment.
- Flex day program providing up to 6 paid days off per year in addition to standard vacations and holidays.
- Internal mentorship program and broad online learning resources such as Udemy.
Tech Stack
Categories
About Nasdaq
Nasdaq builds and operates the Nasdaq Stock Market and multiple U.S. options exchanges, and sells market technology, data, analytics, index, and anti-financial-crime solutions to capital markets and corporates. Its business spans transaction venues, SaaS software, and information services, plus investor relations and ESG reporting tools. Founded in 1971 and headquartered in New York, Nasdaq, Inc. is a public company traded on Nasdaq (ticker: NDAQ) serving customers worldwide.