AI Engineer

Building the Intelligent Cloud of Tomorrow

Location: Mumbai | On-site job

Department: Engineering & AI Practice

Experience: 2 years

Employment Type: Full-Time | Permanent

Reporting To: CEO

Industry: Cloud Technology | AI/ML Services

About NeoNXT Cloud - https://neonxt.com/

NeoNXT is a fast-growing, cloud-native company headquartered in India, specialising in Cloud Migration, Managed Services, Cloud Modernisation, and Hybrid Cloud Solutions. Born with a mission to democratise enterprise-grade cloud capabilities for businesses of all sizes, NeoNXT combines deep technical expertise with a startup's agility and hunger.

At NeoNXT, we don't just move businesses to the cloud we reimagine how they operate in it. As we expand our AI and ML practice, we are looking for engineers who are not just technically brilliant but genuinely passionate about building intelligent systems that solve real problems at scale.

As an AI/ML Engineer at NeoNXT, you will be at the heart of our growing intelligence practice designing, building, and deploying machine learning models and AI-driven solutions on cloud infrastructure. You will work closely with our Cloud and DevOps teams to integrate AI capabilities into client environments, building systems that are not just smart but scalable, secure, and production-ready.

This is a high-impact role where your work will directly shape the AI offerings of NeoNXT and the intelligent cloud journeys of our clients across industries.

Design, build, train and deploy machine learning models for real-world production environments on AWS, Azure or GCP

Develop end-to-end ML pipelines from data ingestion and feature engineering to model training, evaluation and deployment

Build and optimise deep learning models using frameworks such as TensorFlow, PyTorch or Keras

Implement NLP, Computer Vision, Recommendation Systems and Predictive Analytics solutions based on client requirements

Develop and maintain MLOps pipelines using tools like MLflow, Kubeflow, SageMaker or Azure ML

Cloud AI Integration

Deploy and manage AI/ML workloads on AWS (SageMaker, Bedrock, Rekognition), Azure (Azure ML, Cognitive Services) or GCP (Vertex AI)

Integrate AI models into cloud-native applications, APIs and microservices architectures

Collaborate with cloud architects to design scalable, cost-optimised AI infrastructure on hybrid and multi-cloud environments

Leverage serverless and containerised architectures (Docker, Kubernetes) for AI model serving

Work with large-scale structured and unstructured datasets cleaning, transforming and preparing data for modelling

Build data pipelines and feature stores to support model development and retraining

Partner with data engineering teams to design efficient data architectures that support AI workloads

Perform exploratory data analysis, statistical modelling and hypothesis testing

Work directly with NeoNXT's cloud consultants and client stakeholders to understand business problems and translate them into AI solutions

Present model performance, insights and recommendations to both technical and non-technical audiences

Contribute to NeoNXT's AI practice development frameworks, accelerators, reusable components and internal IP

Mentor junior engineers and contribute to a culture of continuous learning and innovation

1 to 2 years of hands-on experience in AI/ML engineering with proven production deployments

Strong programming skills in Python NumPy, Pandas, Scikit-learn, TensorFlow or PyTorch

Solid understanding of machine learning algorithms supervised, unsupervised, reinforcement learning

Experience with cloud ML platforms AWS SageMaker, Anthropic Claude AI, Agora.AI, C3.AI, Cohere, Credo.ai, Scale, Azure ML or Google Vertex AI

Familiarity with MLOps practices model versioning, monitoring, drift detection and retraining pipelines

Experience with containerisation and orchestration Docker and Kubernetes

Strong understanding of data structures, algorithms and software engineering best practices

Experience with REST API development for model serving (FastAPI, Flask)

Excellent problem-solving skills and ability to work in a fast-paced, startup-like environment

Experience with Generative AI, LLMs and prompt engineering (OpenAI, Anthropic, LangChain, RAG architectures)

AWS Certified Machine Learning Specialty or equivalent cloud AI certification

Experience with real-time ML inference and streaming data (Kafka, Kinesis)

Knowledge of hybrid cloud architectures and edge AI deployments

Experience in FinTech, HealthTech, Retail or Manufacturing domains

Open source contributions or published research in AI/ML

Understanding of responsible AI, model explainability (SHAP, LIME) and AI governance

B.Tech / B.E. in Computer Science, Information Technology, Electronics or related field

M.Tech / M.S. in AI, Data Science, Machine Learning or related field preferred but not mandatory

Equivalent demonstrated experience and strong portfolio will be considered over formal qualifications

High Impact Work

Work on real AI problems for enterprise clients across India and globally

Cloud-First Culture

Deep access to AWS, Azure and GCP environments with sandbox and R&D budgets

Career Growth

Fast track growth in a scaling company your contributions directly shape NeoNXT's AI practice

Certification Support

Full support and sponsorship for AWS, Azure, GCP and AI/ML certifications

Competitive Compensation

Market-leading salary, performance bonuses and ESOP opportunities

Flexible & Human Culture

Hybrid work model, flexible hours and a leadership team that genuinely cares

We build for impact not just for technology's sake

We move fast but never sacrifice quality or security

We believe the best cloud solutions are human-centered at their core

We grow together your success is NeoNXT's success

We stay curious the cloud and AI landscape evolves daily and so do we

If you are a builder, a problem-solver and someone who believes that AI on the cloud can genuinely transform how businesses operate we would love to hear from you.

NeoNXT is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.