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).