Nagarro
Principal Engineer, Data Science AI Architect at Nagarro
Nagarro is hiring a Principal Engineer, Data Science AI Architect in Gurugram, Haryana, India. The role details below come from the employer’s posting. You apply on the employer’s own site, and TechJobs360 never charges candidates.
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1. Job details
Nagarro
Principal Engineer, Data Science AI Architect
Gurugram, Haryana, India
Not disclosed by employer
See the job description
On the employer’s site
2. Job description from Nagarro
Company Description
We're Nagarro, we are a Digital Product Engineering company that is scaling in a big way! We build products, services, and experiences that inspire, excite, and delight. We work at scale across all devices and digital mediums, and our people exist everywhere in the world (18000+ experts across 40 countries, to be exact). Our work culture is dynamic and non-hierarchical. We are looking for great new colleagues. That is where you come in!
Job Description
REQUIREMENTS:
Total experience 11+ years.
Must have experience to design, build and run GenAI and Agentic AI solutions inside enterprise systems, fitting AI into existing systems, security rules and budgets.
Must have ability to translate ambiguous business problems into durable technical architectures.
Must have strong ML fundamentals; how models are trained, tested and compared; spotting overfitting and weak data, deep learning basics; embeddings, classification, ranking models
Should be able to architect and implement scalable ML, Generative AI, and Agentic AI solutions (LLMs, RAG, autonomous agents) aligned with business objectives.
Must have experience in data science, ML engineering or AI architecture, with at least 5 years leading ML solutions from design to production.
Should have expertise in Python, SQL and Solid statistics, including outlier detection and error metrics
Should have exposure to time series forecasting.
Should have production experience with regression and tabular ML: feature engineering, model selection, calibration, uncertainty (conformal or quantile intervals) and explainability (SHAP, coefficients).
Must have experience with hierarchical forecasting or reconciliation, and prompt-injection testing.
Should have hands-on experience with embeddings, vector search and hybrid retrieval, and with LLM applications: tool calling, retrieval-grounded generation, citations, guardrails and evaluation.
Should have hands-on experience for building conversational agent, with multi-turn session memory and tool calling into the multiple engines and the semantic layer.
Must have experience on a major cloud: pipelines, model registry, drift monitoring, retraining and low-latency serving.
Should have experience with Google Cloud (Vertex AI, BigQuery, Gemini, Vector Search), or equivalent on another cloud.
Design retrieval-grounded generation with citations, input and output guardrails, human approval for actions, and layered, attack-tested prompt-injection protection
ESPONSIBILITIES:
Understanding the client’s business use cases and technical requirements and be able to convert them into technical design which elegantly meets the requirements.
Lead the design and implementation of complex GenAI workflows that combine LLMs, tools, APIs, structured data, and user context.
Establish engineering standards and best practices for prompt design, model integration, evaluation, and observability.
Drive GenAI platform building reusable components, SDKs, and frameworks used across multiple teams or products.
Partner with product, design, data, and business leaders to translate strategic objectives into scalable technical solutions.
Review critical designs and codebases, unblock teams on complex technical challenges, and raise the overall engineering bar.
Lead technical discovery and solutioning for high-impact initiatives, including client or executive-facing workshops when required.
Ensure enterprise readiness: security, privacy, compliance, governance, and responsible AI practices.
Mapping decisions with requirements and be able to translate the same to developers.
Identifying different solutions and being able to narrow down the best option that meets the client’s requirements.
Defining guidelines and benchmarks for NFR considerations during project implementation
Writing and reviewing design document explaining overall architecture, framework, and high-level design of the application for the developers
Reviewing architecture and design on various aspects like extensibility, scalability, security, design patterns, user experience, NFRs, etc., and ensure that all relevant best practices are followed.
Developing and designing the overall solution for defined functional and non-functional requirements; and defining technologies, patterns, and frameworks to materialize it
Understanding and relating technology integration scenarios and applying these learnings in projects
Resolving issues that are raised during code/review, through exhaustive systematic analysis of the root cause, and being able to justify the decision taken.
Carrying out POCs to make sure that suggested design/technologies meet the requirements.
Qualifications
Bachelor’s or master’s degree in computer science, Information Technology, or a related field.
Service Region: South Asia
3. Skills that usually matter in data and AI roles
General guidance from TechJobs360, not part of Nagarro’s posting. The job description above is what counts for this role.
| Area | What to be comfortable with |
|---|---|
| Languages | Python, SQL, Scala |
| Frameworks & tools | Spark, pandas, PyTorch / TensorFlow, Airflow, a cloud data warehouse |
| Computer science basics | Data structures, algorithms, complexity |
| Ways of working | Version control, code review, testing, reading other people's code |
4. How to prepare for a Principal Engineer, Data Science AI Architect interview
Interview formats differ by company and team, so confirm the rounds with the recruiter. Most hiring loops for roles like this cover:
A recruiter call or an online test. Read the job description twice and be ready to explain how your experience matches it.
Often coding problems on arrays, strings, trees, graphs or dynamic programming, solved while you explain your thinking.
Often design and trade-off questions sized to the role: an API, a component, or a small system.
Answer with the STAR method (Situation, Task, Action, Result). Prepare two or three real stories: a hard problem you solved, a disagreement you handled, and something you learned quickly.
5. Take-home pay example (FY 2026–27, new tax regime)
An example for two common package sizes, not this job’s salary. Under the new tax regime (Section 115BAC) salaried employees get a standard deduction of ₹75,000.
| Component | Example: ₹12 LPA | Example: ₹24 LPA |
|---|---|---|
| Basic salary (40% of CTC) | ₹40,000 / mo | ₹80,000 / mo |
| Employee EPF (12% of basic) | -₹4,800 / mo | -₹9,600 / mo |
| Income tax (TDS) | -₹6,933 / mo | -₹32,450 / mo |
| Professional tax | -₹200 / mo | -₹200 / mo |
| Approx. in-hand | ₹81,344 / mo | ₹1,44,304 / mo |
Work out the take-home pay for your own offer, in either tax regime.
6. Questions and how to apply
How do I apply?
Use the apply button below. It opens Nagarro’s own application page.
Does TechJobs360 recruit for this job or charge a fee?
No. We list openings from employers’ career sites. Nagarro runs the hiring, and nobody should ask you to pay to apply.
Is this job still open?
We check listings against the employer’s page every day and take down jobs that have closed.
Should I apply if I don’t match every requirement?
Usually yes, if you meet most of the core requirements and can show you learn quickly. A referral from someone on the team can help your resume get read.
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