Senior Engineer – Digital Solutions and AI Integration

Responsibilities
Web Application & Software Engineering
Architect & Build Applications: Design, develop, and deploy responsive, high-performance web applications using modern full-stack frameworks (e.g., MERN, MEAN, LAMP, or Java/Spring Boot).
API Development & Integration: Design and implement RESTful APIs, GraphQL endpoints, and microservices to enable seamless communication between front-end interfaces, back-end systems, and third-party tools.
Database Management: Structure, optimize, and maintain relational (SQL), non-relational (NoSQL) and unstructured databases like SharePoint Lists, Excels, etc. to support high-throughput, enterprise-scale applications.
Data Engineering & Business Intelligence
ETL & Data Pipeline Design: Conceptualize, build, and maintain robust ETL/ELT flows to consolidate data from disparate transactional systems, cloud databases, and third-party APIs.
Dashboard & Analytics Engineering: Translate business requirements into intuitive, interactive Power BI dashboards and reports for executive decision-making.
Data Modeling & Governance: Ensure data accuracy, consistency, security, and integrity across relational data models, transactional schemas, and enterprise data marts.
Enterprise Process Automation
Workflow Automation: Identify manual operational workflows and design automated end-to-end process flows using Microsoft Power Automate and custom scripts.
System Integration: Connect enterprise applications (ERP, CRM, legacy databases, web portals) using cloud flows, desktop flows (RPA), and webhooks.
AI & Emerging Technology Integration
Generative & Agentic AI Solutions: Architect and implement solutions incorporating Large Language Models (LLMs), Small Language Models (SLMs), and autonomous Agentic AI frameworks (e.g., LangChain, AutoGen, LlamaIndex).
AI Tooling & Prompt Engineering: Build AI-driven feature enhancements into enterprise web portals and workflow engines to enhance productivity and user experience.
Cloud & DevOps Operations
Cloud Architecture: Deploy, manage, and scale applications and data infrastructure across major public cloud platforms (Microsoft Azure, AWS, or Google Cloud Platform).
CI/CD & Code Hygiene: Implement robust CI/CD pipelines, maintain repository hygiene, conduct code reviews, and enforce security and data compliance standards.
Qualifications
Key Skill Requirements
Hands-on Experience
4 to 8 years of core hands-on experience in full-stack software development, data engineering, and automation solutions.
Software & Web Development Stack
Proficiency in at least one primary full-stack development technology suite:
MERN / MEAN: React.js, Angular, Vue.js, Node.js, Express.js
Java Stack: Java, Spring Boot, Hibernate, Spring MVC
LAMP / Web: PHP, Apache/Nginx, Linux, MySQL, JavaScript/HTML5/CSS3
Data Engineering & Analytics
Experience in designing ETL/ELT processes using tools like Azure Data Factory, AWS Glue, Apache Airflow, or SSIS.
Expert-level proficiency in Power BI (DAX, Power Query, Data Modeling, Security Management, Custom Visuals).
Proficiency with both SQL (PostgreSQL, MS SQL Server, MySQL, Oracle) and NoSQL (MongoDB, DynamoDB, Redis, Cassandra) databases.
Process Automation
Proven track record in building enterprise automation workflows using Microsoft Power Automate (Cloud & Desktop flows).
Cloud Platforms
Practical experience with at least one major cloud provider (Azure, AWS, or GCP), including serverless computing, object storage, managed database services, and IAM policies.
Teamwork, Communication & Execution
Collaboration & Team Player: Demonstrated capability to work effectively within multi-disciplinary & multi-location teams, engaging collaboratively with team members, product managers, vendor partners, UX designers, and business stakeholders.
Interpersonal & Communication Skills: Adept at verbal and written communication, with strong interpersonal skills to translate technical concepts for non-technical leadership and clearly express solution requirements, designs, concepts, etc.
Action-Oriented & Proactive: Highly self-motivated, action-oriented, and proactive in taking ownership, identifying potential roadblocks early, and proposing practical digital solutions.
Preferred Experience
Generative & Agentic AI:
Understanding of LLM/SLM fine-tuning, Retrieval-Augmented Generation (RAG) architectures, and vector databases (e.g., Pinecone, Milvus, ChromaDB, Qdrant).
Familiarity with Agentic AI frameworks (LangChain, LangGraph, AutoGen, CrewAI) and function-calling protocols.
DevOps & Containerization: Experience with Docker, Kubernetes, GitHub Actions, or Azure DevOps for automated building and deployment.
Scripting Languages: Strong proficiency in Python or TypeScript/JavaScript for data processing and AI script integration.
Agile Delivery: Experience working in Agile/Scrum methodologies with cross-functional business, data, and digital product teams.
Problem-Solving & Communication: Exceptional analytical skills with the ability to translate business requirements into technical architectures and articulate tech solutions to non-technical stakeholders.
Preferred Qualification
Primary Qualification: Bachelor’s or Master’s degree in Computer Science, Information Technology, Software Engineering, Data Engineering, or a closely related discipline (B.E. / B.Tech / M.E. / M.Tech / MCA / M.Sc).
Certifications (Desirable):
Cloud: Azure Developer/Data Engineer Associate, AWS Certified Developer/Solutions Architect, or GCP Professional Data Engineer.
Analytics & Automation: Microsoft Certified: Power BI Data Analyst Associate (PL-300) or Power Platform App Maker / Developer (PL-100/PL-400).

Work arrangement
No