Technical Lead – Data Science &

• Generative AI /n Incedo Platform &

• Solutions| Applied AI, Python &

• LLMs /n LOCATION: Gurugram /n EXPERIENCE: 6–10 years /n REPORTS TO: Engineering Manager /n ABOUT INCEDO /n Incedo is a global AI and data transformation specialist, helping companies turn digital investment into sustainable business impact by delivering ROI from AI@Scale. We are 4,000+ people across the US, Canada, Latin America and India, working with Fortune 500 enterprises and fast-growing clients in banking & payments, wealth management, telecom, hi-tech and life sciences. /n Build what's next in AI, data and enterprise platforms /n Our Platform &

• Solutions portfolio is where Incedo builds AI-native products for real enterprise problems: Incedo Lighthouse (AI-powered decision intelligence), DataXel (agentic data modernization), brAInspark (agentic AI enablement), IncedoPay (integrated payables), Kratos (regulatory compliance and data control for banking) and DQXpert (AI-powered data quality) — plus domain products across customer support, document processing, quality engineering, healthcare and financial services. /n WHY THIS ROLE /n This is a builder's role with a leader's remit. You will be hands-on in Python and model code most weeks — and the person the team's work is measured through. /n You decide what "production-ready" means here, and you explain the result to a stakeholder who does not care about your architecture — only whether they can act on it. /n THE ROLE /n As Technical Lead – Data Science &

• Generative AI, you drive the design, development and deployment of machine learning,



deep learning and generative AI solutions across Incedo's platforms and client programmes. /n You work alongside data scientists, data engineers and business stakeholders to ship scalable, production-ready AI/ML applications, shape the technical roadmap for AI initiatives, and mentor the team that builds it. /n WHAT YOU'LL OWN /n 1. Models in production /n /n

- Build, train, tune and deploy ML and deep learning models using TensorFlow or PyTorch and scikit-learn.

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- Own model evaluation, optimisation, monitoring and governance — robustness, fairness, drift and scale, not just offline accuracy.

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- Do the unglamorous work well: preprocessing, wrangling and feature engineering with pandas and NumPy.

/n /n 2. GenAI and LLM applications /n /n

- Develop GenAI applications — conversational agents, summarisation, RAG pipelines, document intelligence.

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- Design retrieval and prompting strategies that hold up on messy enterprise data — and recognise when fine-tuning is the better answer.

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- Instrument outputs so quality is measurable rather than anecdotal.

/n /n 3. Pipelines and engineering rigour /n /n

- Partner with data engineering to design scalable data and model pipelines for training and inference.

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- Enforce reproducibility, testing and code quality across the team's work.

/n /n 4. Leadership and communication /n /n

- Mentor data scientists, run technical reviews and promote coding excellence.

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- Present findings and AI strategy to non-technical stakeholders in language that drives a decision.

/n /n WHAT YOU'LL BRING /n /n

- 6–10 years in data science and applied AI, including experience leading a small technical team.

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- Expert Python: advanced OOP, data structures, API design and testing.

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- Strong ML/DL delivery with TensorFlow and scikit-learn, and fluency in pandas and NumPy.

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- Practical LLM and GenAI experience: Hugging Face Transformers, LangChain or LlamaIndex.

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- Solid statistical foundations: regression, time-series, hypothesis testing and anomaly detection.

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- Communication that bridges technical and business teams — clear, specific and actionable.

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- A proven mentoring record and a bias for shipping over perfecting.

/n /n POSITIVE TO HAVE /n /n

- PyTorch for advanced deep learning and LLM fine-tuning.

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- MLOps in practice: MLflow, Docker, Kubernetes and CI/CD.

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- Vector databases — FAISS, Pinecone, Weaviate or Milvus.

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- Cloud ecosystems (AWS, Azure, GCP) and big data frameworks (Spark, Hadoop).

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- Explainability and fairness tooling such as SHAP and LIME.

/n /n EDUCATION /n B.Tech / M.Tech / M.S. in Computer Science, Statistics, Mathematics or a closely related technical discipline. Equivalent industry experience considered.

📌 Technical Lead - Data Science & Generative AI (Gurugram)
🏢 Incedo
📍 Gurugram