Implement end-to-end statistical/ML/analytics solutions following the industry-standard process, CRISP-DM.
Understand industrial/buildings automation and digital controls.
Develop domain-specific large language models (LLMs).
Build asset lifecycle prediction algorithms.
Understand business requirements and propose suitable solutions.
Explore, devise, and implement AI algorithm stacks.
Design architecture for SaaS offerings.
Software architecture and design.
Implement Observability and Monitoring for software systems.
Code and automate unit and acceptance testing.
Product costing.
Performance tuning and benchmarking.
Product deployment and management.
Product security.
Customer support.
Develop automated UI testing frameworks.
Ability to code in multiple languages.
Strong analytical skills and software development skills.
Integration and certification of software components.
Qualifications:
Required:
BE/BTech/ME/MTech/MCA with 14+ years of experience in SaaS or Software product development.
Strong experience with C# and .NET Core.
Proficient in REST API development.
Work experience in IoT-based cloud application development.
Experience in Azure Cloud-based application development.
Work experience with the Azure ML platform.
Expertise in Data Science, Gen AI, RAG (Agentic AI, LLM), Predictive Modelling (Supervised, Unsupervised), Deep Learning, and NLP.
Tools & Technologies:
Languages: Python, Java
Libraries & Frameworks: Langchain, LangGraph, Scikit-learn, Keras
Data Visualization & UI: Seaborn, Streamlit, Gradio
Databases: SQL (PostgreSQL), Cassandra
Cloud Platforms: Azure, GCP
Other Tools: PowerBI, Git, Docker, Pycharm
We Value:
Extensive SaaS software design & development experience with a minimum of 3-4 complete NPI (New Product Introduction) life cycles.
Hands-on experience in coding, designing, and architecting low-coupled, highly scalable, highly observable, and highly reusable software services and components.
Extensive technical experience in architecting and designing backend services, web and mobile clients, with awareness of contemporary technology paradigms and practices in the SaaS world.
Understanding of native cloud services and offerings from leading vendors, and experience in building cloud vendor-agnostic services and components.
Understanding of resource orchestration software and tools for automating deployment, scaling, and management of containerized applications.
Expertise in building software with world-class SaaS Ops maturity practices, high observability, one-click deployment, and BIC monitoring practices.
Highest focus on quality management tools, code coverage, performance testing, and automated UI tests.
Understanding of product security and applicable tools.
Awareness of designing and architecting software for incubating SaaS offerings, product market fit, pilots, VOCs, and scale strategy.
Good understanding of industrial domain opportunities, existing products, offerings, and evolution.
Ability to engage with end users/customers, partners, and customer relationship management.
Excellent communication skills, including the ability to articulate architecture, technical concepts, and business presentations.
Strong business acumen and understanding of product costing.
Creativity and innovation, with the ability to ideate and drive new solutions.
Work experience in the IoT domain.
A drive to learn and master new technologies and techniques, with a strong team player mindset.
Self-motivated individuals who take initiative and work with minimal supervision, doing things before being asked or forced to do so by events.
Ability to balance demand and capacity when establishing priorities for the organization.
Experience in full-stack development with Microsoft and Open-source technologies (.NET C#, .NET Core, scalable services, RESTful APIs, HTML, CSS3, JavaScript, TypeScript, XML, React, Angular).
Work experience with Docker containerization and microservices-based cloud application development.
