Senior AI Engineer

AI in this role

langchainlanggraphsemantic-kernelbedrocksagemaker

ragai-safety

Job Description Summary

Internal Job Title: Sr. Specialist DDIT US&I AI Engineering

#LI-Hybrid

Location: Hyderabad, India

Relocation Support: Yes

Are you passionate about turning cutting-edge Artificial Intelligence innovations into real-world business impact? As a Sr. Specialist DDIT US&I AI Engineering, you will play a key role in shaping the future of enterprise AI by designing and delivering scalable, secure, and production-ready generative AI and agentic AI solutions. Working at the intersection of cloud engineering, intelligent agents, machine learning, and enterprise data platforms, you will transform complex business opportunities into innovative solutions that improve how we discover insights, automate processes, and create value. This is an exciting opportunity to influence AI strategy, build next-generation capabilities on AWS and Snowflake, mentor engineering teams, and drive the adoption of responsible AI in a highly regulated, global environment.

Job Description

Key Responsibilities

Design and implement production-ready generative and agentic artificial intelligence solutions using Amazon Web Services and Snowflake.
Build secure Retrieval-Augmented Generation solutions with hybrid search, embeddings, reranking, metadata, and enterprise knowledge sources.
Develop intelligent agents using Amazon Bedrock AgentCore, LangChain, LangGraph, Semantic Kernel, and approved orchestration frameworks.
Create secure application programming interfaces and containerized backend services for models, agents, tools, and conversational experiences.
Build document-ingestion pipelines for PDF, Office, HTML, presentation, structured, and unstructured enterprise content.
Develop secure Model Context Protocol clients and servers with authentication, authorization, validation, audit logging, and execution controls.
Integrate Snowflake Cortex AI capabilities with Amazon Web Services applications using governed, secure, and private connectivity patterns.
Implement multi-agent workflows, human review, memory management, task automation, approval controls, and end-to-end traceability.
Establish evaluation, observability, security, responsible artificial intelligence, reliability, performance, and cost-management practices.
Provide technical leadership through reusable architectures, coding standards, design reviews, mentoring, deployment, and operational handover.

Essential Requirements

Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Engineering, or a related field.
8+ years of experience in software engineering, cloud engineering, artificial intelligence, machine learning, or related disciplines.
Proven experience designing and delivering production-grade generative artificial intelligence, Retrieval-Augmented Generation, and agentic artificial intelligence solutions on Amazon Web Services.
Strong proficiency in Python, application programming interface development, secure software engineering, testing, debugging, and containerized services.
Hands-on experience with Amazon Bedrock, Amazon SageMaker, intelligent agent orchestration, document processing, retrieval, grounding, and evaluation frameworks.
Demonstrated expertise in enterprise security, responsible artificial intelligence, observability, reliability, compliance, and technical leadership.

Desirable Requirements

Experience delivering Artificial Intelligence solutions within pharmaceutical, healthcare, life sciences, or other regulated environments.
Advanced expertise with Snowflake Cortex AI, Model Context Protocol frameworks, enterprise agent platforms, or large language model operations practices.

Commitment to Diversity and Inclusion:

Novartis is committed to building an outstanding, inclusive work environment and diverse teams' representative of the patients and communities we serve.

Accessibility and accommodation

Novartis is committed to working with and providing reasonable accommodation to individuals with disabilities. If, because of a medical condition or disability, you need a reasonable accommodation for any part of the recruitment process, or in order to perform the essential functions of a position, please send an e-mail to diversityandincl.india@novartis.com and let us know the nature of your request and your contact information. Please include the job requisition number in your message

Skills Desired

Artificial Intelligence (AI), Biostatistics, Change Management, Curious Mindset, Data Governance, Data Literacy, Data Quality, Data Science, Data Visualization, Deep Learning, Graph Algorithms, Learning Agility, Machine Learning (ML), Machine Learning Algorithms, Python (Programming Language), Stakeholder Engagement, Statistical Analysis, Time Series Analysis

How we rate this

Senior AI Engineer at Novartis rates 94 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

RAGAI SafetyLangChainLangGraphSemantic KernelBedrockSagemaker

Questions you could be asked

How would you design a retrieval step so the model answers from real data instead of guessing?
How do you think about the risk of an AI system in this kind of role failing silently?
What are the limits of LangChain that you've run into, and how did you work around them?
What's a project where you used LangGraph hands-on?
Walk me through how you've used Semantic Kernel in your day-to-day work.

Adapt your resume

List these exact terms on your resume: RAG, AI Safety, LangChain, LangGraph, and Semantic Kernel. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.

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