AstraZeneca

AI & Cloud Solutions Engineer

AstraZeneca Chennai, Tamil Nadu, India

Pharmaceutical Manufacturing · 10,001+ employees

19 h ago
solutions-engineer Senior (5-10 yrs) Full-time India
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About the role

Design, build, and deploy AI-enabled business solutions, agents, and intelligent workflow automation to simplify enterprise processes. Manage cloud infrastructure using Terraform and maintain CI/CD pipelines to ensure secure, scalable, and reliable application delivery.

What they look for

AI Engineering Cloud Engineering DevOps AWS Terraform Python Java JavaScript TypeScript React FastAPI Node.js Generative AI Large Language Models RAG Architectures CI/CD Pipelines

Requirements

Requires a bachelor's or master's degree in a relevant technical field and 4-6 years of experience in cloud, platform, or software engineering. Candidates must possess hands-on experience with AWS, infrastructure automation, and modern development frameworks like Python or JavaScript.

Full description

GCL: C2  

Introduction to role:  

Are you ready to turn enterprise AI into practical outcomes that streamline how we operate and ultimately improve patients’ lives? Do you thrive at the intersection of AI engineering, cloud platforms, and DevOps automation, where ideas move quickly from prototype to production with the right guardrails?

In this role, you will join a high-performing, digitally savvy team that partners across the enterprise to deliver AI assistants, agents, copilots, and intelligent workflow automation. You will work with tools like Veeva AI, Amazon Bedrock, LangChain, Semantic Kernel, MCP, and AWS services. You will build secure and scalable solutions that unlock data value and simplify complex processes.

You will be empowered to spot opportunities, take balanced risks, and shape solutions that make a measurable difference. Your engineering will help accelerate our evolution, from improving how we handle information to creating smarter ways of working for colleagues across the business.  

Accountabilities:  

AI Solution Engineering: Design, build, deploy, and support AI-enabled business solutions, assistants, agents, copilots, and intelligent workflow automation that simplify processes and elevate decision-making.

RAG Architectures: Build and implement Retrieval Augmented Generation solutions using enterprise knowledge and business data to provide trusted answers and speed compliance-ready work.

Enterprise AI Platforms: Evaluate and leverage Veeva AI, Amazon Bedrock, LangChain, Semantic Kernel, MCP, and related services; choose architectures that balance performance, cost, and risk.

Integration Engineering: Develop secure integrations between AI solutions, enterprise applications, SaaS platforms, and data services using APIs and approved integration patterns to enable end-to-end workflows.

Cloud Infrastructure: Provision, configure, and manage AWS services using Infrastructure as Code (Terraform); design for resilience, security, scalability, and cost efficiency.

Cloud-native Delivery: Deploy and support containerized and serverless applications across development, testing, and production environments, with strong release and observability practices.

DevOps and DevSecOps Automation: Build and maintain CI/CD pipelines, infrastructure automation, and controls to improve deployment speed, reliability, and compliance.

Platform Operations and Reliability: Monitor and fix production systems, lead incident remediation, implement SLOs and telemetry, and drive continuous platform improvements.

Security, Data Governance, and Responsible AI: Embed security-by-design, guardrails, and audit ability; operationalize data governance and Responsible AI principles.

Documentation and Standards: Create user documentation, reusable patterns, engineering standards, and solution governance controls for consistent, repeatable delivery.

Partnering and Influence: Collaborate with product owners, architects, and business stakeholders; translate requirements into practical technology solutions and guide the roadmap from MVP to scale.  

Essential Skills/Experience:

  • Bachelor’s or master’s degree or equivalent experience in computer science, IT, Software Engineering, Cloud Computing, AI, or a life sciences subject area, with 4–6 years of relevant experiences in IT
  • Experience in Cloud Engineering, Platform Engineering, DevOps, Software Engineering, Integration Engineering, or Solution Engineering.
  • Experience developing business applications, APIs, or integration solutions.
  • Hands-on experience with AWS cloud services and terraform.
  • Experience developing applications using one or more of Python, Java, JavaScript/TypeScript, React, or similar technologies and modern development frameworks.
  • Experience building REST APIs and backend services using FastAPI, Node.js, or similar frameworks.
  • Good understanding of Generative AI, Large Language Models (LLMs), Prompt Engineering, AI Agents, and RAG architectures.
  • Experience with AI technologies such as Amazon Bedrock, LangChain, Semantic Kernel, MCP, or similar platforms.
  • Experience implementing and supporting CI/CD pipelines.
  • Knowledge of software engineering, testing, security, data governance, and Responsible AI principles.
  • Experience with Git, Docker, infrastructure automation, and cloud-native application delivery.
  • Experience using Jira, Confluence and other Agile DevOps tools

 

Desirable Skills/Experience:

  • Experience with Veeva Vault, Veeva AI, and Veeva platform integrations.
  • Experience building AI agents and agent orchestration solutions.
  • Experience with Amazon Bedrock Agents and Bedrock Knowledge Bases.
  • Experience implementing enterprise-scale RAG solutions.
  • Experience with vector databases and semantic search technologies, developing MCP clients or MCP servers.
  • Experience with Microsoft Power Platform and Power Automate.
  • Experience in Life Sciences, Clinical Development, Regulatory, Quality, or GxP environments.
  • Experience working in supervised and validated environments.
  • AWS, Terraform, Cloud, AI, or related professional certifications.

 

Why AstraZeneca:  

Join a team that blends curiosity with delivery, where your engineering craft directly powers how we serve patients every day. We bring diverse experts together—engineers, product leaders, data specialists, and domain experts—in the same room to unlock bold thinking and move fast with purpose. You will tackle significant problems, apply modern cloud and AI technologies, and see your solutions adopted across a global enterprise. We value kindness alongside ambition, champion ethical and transparent practices, and give you space to own your ideas, make smart decisions, and grow your impact with the support of teammates who challenge and elevate one another.  

Call to Action:  

If you are ready to build and ship AI solutions that matter—at speed and with real ownership—send your CV and show us what you will create next!

We are an equal opportunity employer and value diversity at our company! We do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform crucial job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

Date Posted

04-Sept-2026

Closing Date

17-Sept-2026

AstraZeneca embraces diversity and equality of opportunity.  We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills.  We believe that the more inclusive we are, the better our work will be.  We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics.  We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorization and employment eligibility verification requirements.

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