Lead Consultant - AI Application Engineering

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 Leadership: Partner with data scientists, product managers, and domain experts to frame problems, test hypotheses, and iterate quickly from prototype to production. Lead multi-functional teams across geographies, fostering teamwork, accountability, and high performance. Act as a key partner interface, engaging senior leadership, business units, and external partners.
• Engineering Excellence: Uphold code quality, patterns, and standards; establish CI/CD, testing strategies, and documentation that make solutions maintainable and auditable.
• Innovation and Tech Evaluation: Maintain a clear tech radar; pilot emerging tools and methodologies and scale what works to raise engineering throughput and product impact.
• Operability and Reliability: Ensure robust SLOs, on-call readiness, telemetry, and incident playbooks so applications remain dependable at enterprise scale.
• Capability Building: Mentor engineers, grow skills in AI application engineering, and develop a culture of curiosity, perseverance, and high performance.
• Process, Partner & Vendor Management: Define and implement standardized delivery processes and standards across AI engineering initiatives. Handle partner expectations through structured communication, reporting, and executive-level updates. Establish strong vendor management practices including partner selection, contract governance, performance tracking, and value realization. Ensure compliance with enterprise policies, security standards, and regulatory requirements across all engagements.

Essential Skills/Experience:

• Bachelor’s or Master’s degree in computer science, Engineering, or related field.
• Minimum 12+ years of overall experience in Information Technology, with significant experience in AI/ML engineering and application development.
• Hands-on experience as a Full Stack Developer with a focus on AI and machine learning applications.
• Strong proficiency in programming languages such as Python, JavaScript, or Node.js.
• Experience with frontend frameworks such as React, Angular, or Vue.js and backend technologies including RESTful APIs, Django, or Flask.
• Expertise in machine learning frameworks like PyTorch or Scikit-learn.
• Good experience with Generative AI models and techniques, such as GANs or transformers.
• Experience with OpenAI, bedrock models, cognitive services etc.
• Experience with cloud platforms like AWS, Azure, or Google Cloud, specifically in deploying AI/ML applications.
• Solid understanding of databases such as SQL, NoSQL, and data warehousing solutions like Snowflake.
• Excellent problem-solving skills and the ability to work in a fast-paced, collaborative environment.
• Experience with DevOps practices and tools for continuous integration and deployment (CI/CD).
• Knowledge of microservices architectures and containerization tools like Docker and Kubernetes.
• Familiarity with version control systems such as Git etc.
• Establish and make sure development standards, security protocols, and compliance requirements across custom engineering projects.
• Conduct regular code reviews, performance evaluations, and audits to ensure the integrity and reliability of delivered solutions.
• Collaborate with IT governance teams to ensure alignment to interpersonal policies and standards.

Desirable Skills/Experience:

• Experience in enterprise-level integrations and data engineering projects.
• Familiarity with data visualization tools such as Tableau or Power BI
• Experience leading global delivery models and distributed teams.
• Exposure to regulated industries with strong compliance requirements.
• Prior experience driving AI/ML transformation programs at enterprise scale.

When we put unexpected teams in the same room, we unleash ambitious thinking with the power to inspire life-changing medicines. In-person working gives us the platform we need to connect, work at pace and challenge perceptions. That's why we work, on average, a minimum of three days per week from the office. But that doesn't mean we're not flexible. We balance the expectation of being in the office while respecting individual flexibility. Join us in our unique and ambitious world.

Why AstraZeneca:

Here, engineering talent meets scientific purpose. You will work with advanced platforms, real-world data, and ambitious collaborators to deliver AI capabilities that tangibly speed research, sharpen decision-making, and expand access for patients. Backed by significant investment and a bold digital vision, we pair high standards with freedom to experiment—think hackathons, rapid pilots, and scaling what works—so you can build, learn, and lead. We value perseverance alongside ambition, encourage clear debate, and bring diverse expertise together to solve problems that matter at global scale.

Call to Action:

Lead the next wave of AI application engineering that moves medicines to patients faster—submit your application and start creating impact this quarter.

Date Posted

Closing Date

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.