AstraZeneca

Pharmaceuticals

LeadConsultant-AIApplicationEngineering

₹35–55L ~AI est. Bangalore, Karnataka, India FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Lead candidates.

The Brief

“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.

Pharmaceuticals
Problems you'll solve

Problem-solving; Root cause analysis; Troubleshooting; Hypothesis testing

Eligibility Requirements

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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