Senior AI Engineer

Takeda; Bengaluru; On-site; INR 4,500,000 - 7,500,000; Full time

Benefits offered by this job

Competitive Salary + Performance Bonus

Flexible work environment

Healthcare Insurance

Group Life Insurance

Employee Assistance Program

Learning platforms

Diversity & Inclusion Programs

Home Internet & Mobile Reimbursements

Employee Referral Program

Parental Leave

Job summary

Takeda in Bengaluru seeks a Senior AI Engineer to own end-to-end GenAI and agentic AI initiatives across the product lifecycle, from problem framing to production deployment. You will design scalable architectures, drive governance, observability, and cost controls, and collaborate with global teams to deliver enterprise-grade AI capabilities.

The role requires hands-on development across data pipelines, backend services, and sometimes UI components, with a strong emphasis on responsible AI,

Qualifications

• Bachelor’s degree in computer science, engineering, data science, or related field.
• 6+ years of relevant experience in Data Science, AI engineering, or related fields.
• Hands-on experience building and deploying Generative AI/Agentic AI solutions in enterprise environments.
• Experience using Databricks and AWS, with CI/CD automation via GitHub Actions.
• Strong proficiency in Python and modern ML frameworks (PyTorch/TensorFlow).
• Deep understanding of NLP, transformers, embeddings, vector databases, and RAG architecture.
• Ability to manage AI solutions for scalability, reliability, and cost efficiency.

Responsibilities

• Design end-to-end GenAI and agentic AI solutions, including RAG pipelines and multi-step reasoning.
• Translate business problems into scalable AI architectures spanning data, model orchestration, and apps.
• Lead end-to-end AI solution development across data pipelines, APIs, and UI components when needed.
• Define reference architectures for GenAI components and review designs for best practices.
• Collaborate with global stakeholders to accelerate enterprise-wide AI adoption.
• Establish automated deployment strategies and GenAI observability.

Skills

Python

NLP

AI engineering

Communication

Cross-functional collaboration

CI/CD automation

Education

Bachelor’s degree in computer science, engineering, data science, or related field

Tools

Databricks

AWS

GitHub Actions

Langchain

Langflow

PyTorch

TensorFlow

RAG architecture

Job description

Job Description

The Future Begins Here:

At Takeda, we are leading digital evolution and global transformation. By building innovative solutions and future-ready capabilities, we are meeting the need of patients, our people, and the planet.

At Takeda’s ICC we Unite in Diversity:

Takeda is committed to creating an inclusive and collaborative workplace, where individuals are recognized for their backgrounds and abilities they bring to our company. We are continuously improving our collaborators journey in Takeda, and we welcome applications from all qualified candidates. Here, you will feel welcomed, respected, and valued as an important contributor to our diverse team

About the role :

As a Senior AI Engineer, you will provide deep hands-on technical ownership in designing, building, and operationalizing scalable enterprise-grade Generative AI and Agentic AI solutions that deliver trusted, actionable intelligence across the business. You will help establish strong engineering standards for AI development, including structured experimentation, evaluation rigor, secure deployment, and reliable production operations, ensuring AI capabilities are delivered responsibly and at enterprise quality.

You will lead the end-to-end lifecycle of AI implementation from problem framing and proof-of-concept through production deployment, monitoring, and continuous optimization embedding governance, observability, performance efficiency, and cost control into solution design. You will lead the end-to-end lifecycle of AI solutions from problem framing and proof-of-concept through production deployment, monitoring, and continuous optimization embedding governance, observability, performance efficiency, and cost control into solution design & implementation. This is a hands-on builder role requiring true ownership of AI-powered solutions across the product lifecycle. The ideal candidate is well-rounded and willing to contribute beyond model development, including data engineering, backend services, application logic, and user-facing components where needed to ensure reliable, scalable production outcomes.

You will collaborate closely with AI product lead, Solution & Design Leads, Delivery Leads, platform teams, and global PDT DD&T stakeholders across India, Europe, and the United States to accelerate modern AI adoption and enterprise-wide value realization.

This role reports to Delivery lead and is aligned with the Data & Analytics chapter within ICC.

How will you contribute:

Gen-AI Solutioning & Delivery:

• Design and implement end-to-end LLM-powered Generative AI and Agentic AI solutions, including RAG pipelines, agentic workflows, and multi-step reasoning systems.


• Translate business problems into scalable AI architectures spanning data, retrieval, model orchestration, and application layers. Ensure clear alignment on success metrics & business value with Product leads


• Hands-on leadership & contribution for end-to-end AI solution development spanning data pipelines, service-layer APIs, application integration, and UI enablement, in addition to model, prompt, and framework engineering, to deliver scalable production systems.


• Define and maintain reference architectures for GenAI components—RAG pipelines, agentic systems, vector storage, and scalable inference endpoints


• Review solution designs and technical approaches created by junior engineers, ensuring alignment to architectural best practices and enterprise engineering standards. Includes evaluating use of agent frameworks (LangGraph, CrewAI, Swarm), validating tooling abstractions, memory strategies, and multiagent collaboration patterns.


• Deliver in a globally distributed ecosystem, need to collaborate across Business users, Product lead, Solution & Design leads, Enterprise Architecture teams, Platform teams & other engineering, dev teams

Retrieval, Context Engineering & Agentic Systems:

• Build and optimize retrieval pipelines using vector databases, hybrid search, reranking, grounding, and provenance tracking.


• Develop agent orchestration patterns, tool integrations, and context-management strategies for long-running or multi-agent workflows.


• Ensure freshness, accuracy, and traceability of knowledge used in AI-generated outputs.

Model Development, Tuning & Optimization:

• Evaluate and select foundation models across cloud and self-hosted environments.


• Implement fine-tuning, parameter-efficient adaptation, and prompt optimization strategies.


• Improve latency, scalability, and cost efficiency using batching, caching, distillation, or quantization techniques.

Infrastructure, Deployment & Observability:

• Collaborate with Infrastructure and Platform teams to enable scalable, secure, and cost-efficient cloud infrastructure supporting Generative AI and agentic workloads across development, testing, and production environments.


• Establish automated deployment strategies for Gen-AI services.


• Implement monitoring for quality, hallucinations, drift, latency, and system reliability. Define rollback, governance, and lifecycle management processes for AI and agentic systems


• Ensure strong GenAI observability across all solutions, including prompt tracing, metrics instrumentation, log reduction, quality monitoring, and operational telemetry.

Engineering ownership & excellence:

• Design, build, and maintain scalable data pipelines, backend services, and APIs that power AI-driven applications and production workflows.


• Contribute to frontend or user experience components where needed to deliver intuitive, reliable, and production-ready AI solutions.


• Apply strong software engineering best practices across the product implementation lifecycle, including version control, CI/CD automation, testing strategies, code quality, and comprehensive documentation


• Demonstrate flexibility to contribute beyond core GenAI development, supporting adjacent engineering domains to ensure true end-to-end solution delivery and operational success.

Responsible AI, Security & Compliance:

• Adhere to privacy, security, and ethical AI standards across data, prompts, models, and outputs.


• Implement guardrails, content filtering, access control, and human-in-the-loop review where required.


• AI solutions aligned with regulatory expectations and enterprise governance frameworks.


• HIPAA/GDPR audits; model cards documenting bias testing (demographic parity <0.8), lineage tracing.


• PII anonymization, access controls (RBAC/IAM) for datasets/models.


• Protect against adversarial attacks (prompt injection, evasion); robustness testing (Adversarial Robustness Toolbox)

Innovation & Enablement:

• Continuously evaluate emerging Gen-AI technologies and guide adoption strategy.


• Act as a strong advocate for responsible and high-impact AI adoption across the team


• Educate stakeholders on AI capabilities, limitations, and best practices, enabling informed and ethical usage.


• Drive reusable AI patterns, playbooks, and internal enablement programs to accelerate scalability & maturity.


• Mentor peers, fostering a culture of experimentation, learning, and engineering excellence in AI.


• Contribute to shaping AI long-term capability roadmap.

Requirements :

• Bachelor’s degree in computer science, Engineering, Data Science, or related field.


• 6+ years of relevant experience in Data Science, Machine Learning, AI engineering.


• Hands-on experience building and deploying Generative AI or Agentic AI solutions in enterprise environments, from POC through production.


• Proven hands-on experience building and deploying AI/ML solutions using Databricks and AWS, with CI/CD automation through GitHub Actions for reliable, production-grade releases.


• Strong proficiency in Python, modern ML frameworks such as PyTorch or TensorFlow, modern AI orchestration frameworks such as Langchain, Langflow


• Demonstrated experience delivering production-grade AI-powered applications end-to-end, contributions in aspects including data engineering, backend services, and application or UI components.


• Deep understanding of NLP, transformers, embeddings, vector databases, and RAG architecture. Experience deploying scalable AI services on cloud infrastructure. Strong knowledge of monitoring, model lifecycle management, and evaluation frameworks.


• Understanding of Responsible AI, privacy, security, and governance in regulated environments.


• Demonstrated ability to manage AI solutions for scalability, reliability, and operational cost efficiency.


• Excellent problem-solving, communication, and cross-functional collaboration skills in global teams.

Preferred Skills :

• Relevant AI focused professional degree, certifications


• Experience designing and implementing multi-agent AI systems


• Experience defining AI Total Cost of Ownership (TCO), ROI measurement, and enterprise adoption strategy.


• Proven track record of mentoring teams and championing modern AI engineering practices.


• Background in healthcare, life sciences, or other regulated industries.


• Experience in MCP, Agent2Agent communication protocols

BENEFITS:

• Competitive Salary + Performance Annual Bonus


• Flexible work environment, including hybrid working


• Comprehensive Healthcare Insurance Plans for self, spouse, and children


• Group Term Life Insurance and Group Accident Insurance programs


• Employee Assistance Program


• Broad Variety of learning platforms


• Diversity, Equity, and Inclusion Programs


• Reimbursements – Home Internet & Mobile Phone


• Employee Referral Program


• Leaves – Paternity Leave (4 Weeks) , Maternity Leave (up to 26 weeks), Bereavement Leave (5 calendar days)

ABOUT ICC IN TAKEDA:

• Takeda is leading a digital revolution. We’re not just transforming our company; we’re improving the lives of millions of patients who rely on our medicines every day.


• As an organization, we are committed to our cloud-driven business transformation and believe the ICCs are the catalysts of change for our global organization.

Locations:

IND - Bengaluru

Worker Type:

Employee

Worker Sub-Type:

Regular

Time Type:

Full time