Engineer
Posted 7 Sep 2026
Advertised as “Senior Engineer – Digital Solutions and AI Integration”
BranchFactor Summary
The original posting with the fluff stripped out
- Expected experience
- 4–8 yrs
- Management level
- Individual contributor
Compensation
No salary listed for this role.
Role speciality
Artificial Intelligence IntegrationBusiness IntelligenceCloud ArchitectureData EngineeringDigital SolutionsFull-stack Software DevelopmentProcess Automation
Useful technologies
AngularApacheApache AirflowAutoGenAWSAWS Certified DeveloperAWS Certified Solutions ArchitectAWS GlueAzureAzure Data FactoryAzure DevOpsCassandraChromaDBCrewAICSS3DAXDockerDynamoDBExcelExpress.jsGCPGCP Professional Data EngineerGitHub ActionsGoogle Cloud PlatformGraphQLHibernateHTML5JavaJavaScriptKubernetesLAMPLangChainLangGraphLinuxLlamaIndexMEANMERNMicrosoft AzureMicrosoft Certified: Power BI Data Analyst AssociateMicrosoft Power AutomateMilvusMongoDBMS SQL ServerMySQLNGINXNode.jsOraclePHPPineconePL-100PL-300PL-400PostgreSQLPower BIPower QueryPythonQdrantReact.jsRedisRESTSharePoint ListsSpring BootSpring MVCSSISTypeScriptVue.js
Preferred qualifications
CertificationsAWS Certified Developer, GCP Professional Data Engineer, Microsoft Certified: Power BI Data Analyst Associate, PL-300, PL-100, PL-400
Field of studyComputer Science, Data Engineering, Information Technology, Software Engineering (or related)
Study levelBachelor's or higher
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).