- *Job Description:**
- -------------------
- *Job Title: AI Engineer (Generative AI / LLM Platform \& Enablement), AVP**
- *Location: Bangalore, India**
- As an AI Engineer in the AI Enablement Team, you will design and deliver enterprise‑grade capabilities that enable teams to adopt Generative AI safely and effectively. You will operate across platform engineering and applied GenAI development, while acting as a trusted advisor to engineers and business users—translating emerging AI capabilities into practical, scalable solutions that drive real business impact.
As part of our flexible scheme, here are just some of the benefits that you’ll enjoy
- Best in class leave policy
- Gender neutral parental leaves
- 100% reimbursement under childcare assistance benefit (gender neutral)
- Sponsorship for Industry relevant certifications and education
- Employee Assistance Program for you and your family members
- Comprehensive Hospitalization Insurance for you and your dependents
- Accident and Term life Insurance
- Complementary Health screening for 35 yrs. and above
- *Your key responsibilities**
Build and Evolve the GenAI Platform
- Develop reusable platform components for LLM access, orchestration, and agent\-based workflows.
- Design and implement **RAG and CAG patterns** , including ingestion pipelines, retrieval strategies, and context assembly to ensure high\-quality grounded outputs.
- Establish reusable **prompting frameworks** , templates, and standards to enable consistent and scalable use of GenAI across the organization.
Apply GenAI Fundamentals in Practice
- Demonstrate strong understanding of **Generative AI core concepts** , including:
+ Prompt engineering (structured prompting, system prompts, optimization)
+ Retrieval\-Augmented Generation ( **RAG** ) and Context\-Augmented Generation ( **CAG** )
+ Programmatic prompting approaches (e.g., **DSPy** )
- Translate these concepts into robust, production\-ready implementations, and reusable patterns for others.
Work Across End\-User and Developer Ecosystems
* Leverage and integrate both
+ **End\-user oriented tools** such as Microsoft Copilot, Copilot Studio, and AI Builder
+ **Developer\-oriented frameworks and platforms** such as Python, LangChain, Vertex AI, and Snowflake Cortex AI
- Optionally contribute to broader engineering stacks (e.g., Java, Spring AI, React) where needed.
- Actively use and promote **coding copilots** (e.g., GitHub Copilot, Gemini Code Assist, Claude Code) to accelerate development and improve engineering productivity.
Enablement and Consulting Mindset
- Act as a **consultant within the organization** , helping teams maximize the value of existing tools and platforms rather than defaulting to bespoke builds.
- Support engineers and business users in understanding **how and where GenAI delivers value and** guide them towards pragmatic solution patterns.
- Create reusable assets such as reference architectures, starter kits, and best practices.
- Communicate complex technical concepts in a clear, actionable way for both technical and non\-technical audiences.
Quality, Governance, and Operational Excellence
- Implement evaluation, observability, and quality frameworks for LLM applications.
- Ensure solutions meet enterprise standards for reliability, security, and responsible AI adoption.
- Align with governance, risk, and compliance requirements in regulated environments.
- *Your skills and experience**
Core Technical Expertise
- Strong software engineering foundation (Git, Agile, Python, Streamlit, APIs, TDD, CI/CD).
- Hands\-on experience with **LLM applications and platforms** (e.g., Vertex AI, Cortex AI, LangChain, LangGraph, LangFuse or similar).
- Solid, practical understanding of:
- Prompt engineering and prompt lifecycle management
- **RAG / CAG architectures**
- Evaluation approaches for GenAI systems
- Observability and operationalisation of AI solutions
Tooling \& Ecosystem Breadth
* Experience in at least one of the following
+ **End\-user AI tools** (e.g., Microsoft Copilot, Copilot Studio, AI Builder)
+ **Developer\-focused AI frameworks** (e.g., Python, LangChain, Google Vertex AI, Snowflake Cortex AI)
- Familiarity with other modern development stacks (Java, Spring, Typescript, React, Vite, TanStack) is a strong plus.
- Practical use of **coding copilots** (GitHub Copilot, Gemini Code Assist, Claude Code, OpenCode) to accelerate development workflows.
Ways of Working
* Strong **consulting mindset** with the ability to
+ Identify high\-impact use cases
+ Guide teams toward pragmatic, scalable solutions
+ Balance speed, quality, and governance
- Excellent communication and stakeholder engagement skills across technical and non\-technical audiences.
- Ability to work beyond pure engineering—focusing on enablement, adoption, and measurable impact.
### **What Success Looks Like**
- Widely adopted **GenAI platform capabilities and reusable patterns** across teams.
- Clear improvement in **time\-to\-value for AI use cases** through effective enablement.
- Consistent application of **prompting standards, RAG/CAG patterns, and evaluation practices** .
- Strong adoption of both **developer and end\-user AI tooling** , maximizing the value of the existing ecosystem.
- Training and development to help you excel in your career
- Coaching and support from experts in your team
- A culture of continuous learning to aid progression
- A range of flexible benefits that you can tailor to suit your needs
- *About us and our teams**
Please visit our company website for further information
- *https://www.db.com/company/company.html**
We at DWS are committed to creating a diverse and inclusive workplace, one that embraces dialogue and diverse views, and treats everyone fairly to drive a high\-performance culture. The value we create for our clients and investors is based on our ability to bring together various perspectives from all over the world and from different backgrounds. It is our experience that teams perform better and deliver improved outcomes when they are able to incorporate a wide range of perspectives. We call this \#ConnectingTheDots.