Senior Engineer – Digital Solutions and AI Integration

Purpose/Objective

We are seeking a versatile and highly skilled Senior Engineer – Digital Solutions & AI Integration with 4 to 8 years of hands-on experience in building scalable digital systems, end-to-end data pipelines, and intelligent automation workflows.
In this role, you will bridge the gap between software engineering, data management, enterprise automation, and cutting-edge artificial intelligence.
You will work with the development team to design, develop, and deploy enterprise web applications, establish robust ETL pipelines, create actionable analytics dashboards in Power BI, automate business processes using Power Automate, and integrate modern Generative AI and Agentic AI architectures.
If you thrive in a fast-paced environment and enjoy solving complex enterprise challenges across multi-cloud and multi-stack environments, this role offers an exciting opportunity to drive impactful digital transformation.

Key Responsibilities of Role

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.

Technical Competencies

Software & Web Development Stack,Data Engineering & Analytics (ETL, PowerBi, SQL),Power Automate,Cloud Platform (Azure / AWS / GCP)

Qualifications and Experience

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).