AstraZeneca
Pharmaceuticals
LeadConsultant-AIApplicationEngineering
Neural analysis suggests this role is
optimal for Lead candidates.
“Lead Consultant - AI Application Engineering at AstraZeneca. Skills: AI Application Engineering, Generative AI, Full-Stack Delivery, MLOps. Define technical direction for AI applications. Make pragmatic build-versus-buy choices”
What You'll Achieve.
Deliver measurable outcomes; Raise engineering throughput; Increase product impact; Ensure applications remain dependable; Deliver AI capabilities; Speed research; Sharpen decision-making; Expand patient access; Move medicines to patients faster
Industry & Context.
Problem-solving; Root cause analysis; Troubleshooting; Hypothesis testing
On-call readiness
What They're Looking For.
Must Have
12+ years of IT experience, Significant AI/ML engineering experience, Significant application development experience, Hands-on Full Stack Developer experience, Python programming proficiency, JavaScript programming proficiency, Node.js programming proficiency, Frontend framework experience, Backend technology experience, RESTful APIs experience, Django experience, Flask experience, Machine learning frameworks expertise, Generative AI models experience, Generative AI techniques experience, OpenAI experience, Bedrock models experience, Cognitive services experience, Cloud platforms experience, Deploying AI/ML applications experience, SQL database knowledge, NoSQL database knowledge, Data warehousing solutions knowledge, DevOps practices experience, CI/CD tools experience, Microservices architectures knowledge, Containerization tools knowledge, Git version control experience, Establish development standards, Establish security protocols, Establish compliance requirements, Conduct code reviews, Conduct performance evaluations, Conduct audits, Collaborate with IT governance teams
Nice to Have
Enterprise-level integrations experience, Data engineering projects experience, Data visualization tools familiarity, Leading global delivery models experience, Distributed teams experience, Regulated industries experience, AI/ML transformation programs experience
What You'll Do.
Define technical direction for AI applications
Make pragmatic build-versus-buy choices
Lead end-to-end engineering
Deliver resilient applications
Deliver observable applications
Deliver secure applications
Operationalize models
Ensure model accuracy
Ensure model reliability
Apply LLMs to create experiences
Apply LLMs to automate workflows
Design for performance
Design for elasticity
Ensure safe use of AI
Partner with data scientists
Partner with product managers
Partner with domain experts
Lead multi-functional teams
Foster accountability
Foster high performance
Engage senior leadership
Engage business units
Engage external partners
Establish testing strategies
Establish documentation
Pilot emerging methodologies
Scale successful tools
Scale successful methodologies
Ensure on-call readiness
Ensure incident playbooks
Grow AI application engineering skills
Develop culture of curiosity
Develop culture of perseverance
Develop culture of high performance
Define delivery processes
Implement delivery processes
Define delivery standards
Implement delivery standards
Handle partner expectations
Communicate structured reporting
Provide executive-level updates
Establish vendor management practices
Track vendor performance
Ensure compliance with enterprise policies
Ensure compliance with security standards
Ensure compliance with regulatory requirements
How You'll Work.
Team & Collaboration
Multi-functional squads; Multi-functional teams; Cross geographies; Senior leadership engagement; Business unit engagement; External partner engagement; IT governance teams
Communication Scope
Executive-level updates; Structured communication; Reporting
Process & Methodology
Agile, Product leadership, Delivery processes, Delivery standards, Vendor management
Full Job Description
**Job Title:** Lead Consultant - AI Application Engineering **Career Level:** E **Location:** Bangalore ## ## Introduction to role: Are you ready to turn modern AI into reliable, scalable applications that help accelerate the discovery and delivery of life-changing medicines? Do you thrive at the intersection of hands-on engineering, GenAI, and product leadership—translating ideas into tools that scientists and business teams use every day? In this role, you will lead full-stack delivery of AI-enabled products from architecture to production, applying modern engineering practices to unlock data, automate decisions, and create seamless user experiences. You will guide multi-functional squads, shape technical direction, and ship secure, high-quality solutions that scale across a global enterprise. With strong sponsorship and access to sophisticated platforms, you will set the pace for how AI is designed, built, and embraced. In addition, you will be responsible for ensuring alignment of AI initiatives with business strategy, driving operational excellence, and leading high-performing teams to deliver measurable outcomes at scale. ## ## Accountabilities: * Product Architecture and Strategy * Define technical direction for AI applications, making pragmatic build-versus-buy choices. * Full-Stack Delivery: Lead end-to-end engineering across front-end, back-end, APIs, data layers, and infrastructure to deliver resilient, observable, and secure applications. * Machine Learning Pipelines: Operationalize models with robust data ingestion, feature stores, evaluation, and monitoring to ensure accuracy, reliability, and drift management. * Generative AI Integration: Apply LLMs and related techniques (prompting, fine-tuning, retrieval) to create new user experiences and automate knowledge-heavy workflows responsibly. * Scalable Systems: Design for performance and elasticity, optimizing cost and latency while ensuring compliance, privacy, and safe use of AI. * Teamwork and Leaders
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