AI and Data Engineering Tech Lead

Carelon Global Solutions; Bengaluru; On-site; INR 4,500,000 - 7,500,000; Full time

Job summary

Carelon Global Solutions in Bengaluru/Gurugram seeks a Tech Lead III – AI to design and implement scalable data pipelines, optimize ML models, and lead cross-functional teams across data science and product management.

You will work with Kubernetes, MLflow, DVC, PyTorch/TensorFlow, and LLM deployment, ensuring enterprise-grade reliability and cost efficiency. This is a full-time role in a dynamic AI environment.

Qualifications

• Bachelor's degree in Engineering (CS/Engineering preferred).
• 5+ years of AI engineering experience; total 8–12+ years preferred.
• Proficiency in Python and data science libraries (NumPy, Pandas) and deep learning frameworks (PyTorch, TensorFlow).
• Experience with large-language-model frameworks (Hugging Face Transformers) and prompt engineering.
• Proficiency with Spark for large-scale analytics.
• Experience with version control (Git) and experiment tracking (MLflow, DVC).
• Strong software engineering background: microservices, TDD, concurrency; Go or Rust is advantageous.
• DevOps skills: IaC (Terraform, CloudFormation), CI/CD (GitHub Actions, Jenkins), Kubernetes with Helm, containerization.
• LLM infra and deployment: vLLM, FastAPI, TorchServe, model quantization, vector DBs.
• MLOps: retraining, serving, monitoring; cloud platforms (AWS, GCP, Azure).

Responsibilities

• Collaborate with data scientists and product teams to acquire and manage data for AI/ML model integration.
• Design, implement, and maintain scalable data pipelines for AI/ML models.
• Debug, optimize, and enhance ML models with QA and performance improvements.
• Operate Kubernetes and service mesh for scalable ML workloads.
• Design and build scalable LLM inference architectures with GPU memory optimization.
• Engage in prompt engineering and fine-tuning of LLMs for semantic retrieval and chatbots.
• Document architectures, experiments, and results with MLflow or DVC.
• Research and implement LLM optimization techniques like quantization and distillation.
• Collaborate with stakeholders to develop NLP solutions (text classification, sentiment analysis, topic modelling).
• Stay up-to-date with AI trends and deploy innovative methodologies across healthcare AI solutions.

Skills

Python

NumPy/Pandas

PyTorch/TensorFlow

Hugging Face

Spark

Git

MLflow/DVC

Kubernetes

Terraform

Go/Rust

NLP/LLM

Education

Bachelor's in Engineering (CS/Engineering)

Tools

MLflow

DVC

TorchServe

vLLM

FastAPI

Job description

Tech Lead III – AI (AI and Data Engineering) – Full‑time – Bangalore / Gurugram.

Job Responsibilities

• Collaborate with data scientists, product managers, and cross‑functional teams to acquire, process, and manage data for AI/ML model integration and optimization.
• Design, implement, and maintain robust, scalable, enterprise‑grade data pipelines to support state‑of‑the‑art AI/ML models.
• Debug, optimize, and enhance machine learning models, ensuring quality assurance and performance improvements.
• Operate container orchestration platforms such as Kubernetes with advanced configurations and service mesh implementations for scalable ML workload deployments.
• Design and build scalable LLM inference architectures, employing GPU memory optimization techniques and model quantization for efficient deployment.
• Engage in advanced prompt engineering and fine‑tuning of large language models (LLMs) focusing on semantic retrieval and chatbot development.
• Document model architectures, hyperparameter optimization experiments, and validation results using version control and experiment tracking tools like MLflow or DVC.
• Research and implement cutting‑edge LLM optimization techniques such as quantization and knowledge distillation to reduce computational costs and improve efficiency.
• Collaborate closely with stakeholders to develop innovative and effective natural language processing solutions, specializing in text classification, sentiment analysis, and topic modelling.
• Stay up‑to‑date with industry trends and advancements in AI technologies, integrating new methodologies and frameworks to continually enhance the AI engineering function.
• Contribute to creating specialised AI solutions in healthcare, leveraging domain‑specific knowledge for task adaptation and deployment.

Qualifications

• Bachelor’s degree in Engineering (Computer Science/Engineering preferred); advanced degrees or certifications are a plus.
• 5+ years of relevant experience in AI engineering; total ten‑year experience ranging from 8 to 12+ years is preferred.
• Advanced proficiency in Python with strong knowledge of data science libraries (NumPy, Pandas, scikit‑learn) and deep learning frameworks (PyTorch, TensorFlow).
• Extensive experience with large‑language‑model frameworks (Hugging Face Transformers, LangChain) and prompt engineering techniques.
• Proficiency in big‑data processing using Spark for large‑scale analytics.
• Experience with version control (Git) and experiment tracking (MLflow, DVC).
• Strong background in software engineering: microservices, test‑driven development, concurrency, and Go or Rust is advantageous.
• DevOps and infrastructure skills: Infrastructure as Code (Terraform, CloudFormation), CI/CD pipelines (GitHub Actions, Jenkins), Kubernetes with Helm and service mesh, and containerization practices.
• LLM infrastructure and deployment knowledge: serving platforms such as vLLM, FastAPI, TorchServe, TFS, model quantization, and vector database management.
• MLOps expertise: automated model retraining, model serving, and monitoring.
• Advanced cloud platform knowledge (AWS, GCP, Azure) and network security for ML systems.

Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender identity or expression, sexual orientation, national origin, genetics, pregnancy, disability, age, veteran status, or other characteristics. Reasonable accommodation is available upon request.