Jobs at RevStar Consulting

Build responsive React frontends and secure, scalable NodeJS and Express backends for cloud-native client applications. Integrate structured and unstructured data across AWS services, implement search and ETL pipelines, optimize performance, and contribute to architecture, APIs, testing, code reviews, and shared components. Collaborate in Agile teams, work directly with clients, gather requirements, demo solutions, and ensure delivery meets business goals.

Build and optimize cloud-agnostic Databricks Lakehouse architectures, scalable ETL/ELT pipelines, and MLOps frameworks across AWS, Azure, and GCP. Tune Spark workloads, automate deployments with CI/CD and Infrastructure-as-Code, and implement monitoring, data quality, governance, security, and compliance controls. Partner with data scientists, architects, ML engineers, and client stakeholders to productionize AI/ML models and deliver enterprise data solutions.

Design and optimize Databricks Lakehouse architectures and scalable ETL/ELT pipelines across AWS, Azure, and GCP. Build Spark and Delta Lake workflows for structured and unstructured data, tune performance and cloud costs, and integrate MLflow for AI model operationalization. Implement CI/CD and infrastructure-as-code deployments, enforce governance and security through Unity Catalog, and collaborate with client leaders to deliver production-ready data and AI solutions.

Lead hands-on software engineering across delivery teams by writing production code, governing architecture, reviewing code, and establishing standards for ReactJS, NodeJS, and AWS systems. Build reusable engineering accelerators, drive AI adoption, conduct project audits, and develop technical training. Mentor senior engineers and collaborate with product, DevOps, and QA leaders to align technical decisions with business outcomes.

Lead end-to-end AWS migration engagements from discovery through stabilization. Manage technical delivery, client relationships, scope, risks, timelines, escalations, team allocations, and delivery governance. Collaborate with Solutions Architects, Engineering, DevOps, QA, Product, Sales, and clients on migration strategies, dependency mapping, backlog refinement, estimation, cutover planning, quality gates, and follow-on modernization opportunities.

Lead pre-sales technical discovery and serve as the primary architectural authority for enterprise AWS AI/ML, data, and cloud modernization initiatives. Design Bedrock and SageMaker solutions, migration strategies, and modern data platforms; develop AWS cost models, SOWs, proposals, and funding inputs; evaluate risks and compliance requirements; and coordinate technical handoffs with delivery teams. The role partners with account executives, AWS field teams, customers, and internal engineers without carrying a sales quota.

Own AWS co-sell opportunities from partner referral through contract closure. Build relationships with AWS account teams, qualify cloud modernization and application opportunities, lead business discovery, maintain accurate HubSpot and AWS ACE pipeline data, coordinate proposals and SOWs with Solutions Architects, and develop enterprise account expansion strategies. The role requires B2B technology sales experience and familiarity with partner-led channel ecosystems, with AWS and incentive-program experience preferred.

Own end-to-end product delivery for enterprise clients, from discovery and roadmap definition through launch. Lead client workshops, create PRDs and prioritized backlogs, guide Agile cross-functional teams, manage Azure DevOps governance, and communicate with executives. Use generative AI and rapid-prototyping tools to validate experiences and accelerate delivery. Serve as the primary client contact while managing scope, risks, technical tradeoffs, and account growth.

Design, build, and deploy production-ready LLM APIs and GenAI solutions on AWS. Implement RAG pipelines, data lake pipelines, serverless workflows, prompt orchestration, and AI dashboards. Collaborate with product, DevOps, and architecture teams, document solutions, and support client handoffs while staying current with AWS GenAI and MLOps innovations.

Design and build responsive React frontends and scalable Node/Express backends. Implement search and ETL pipelines, integrate data sources on AWS, translate Figma designs into reusable UI components, optimize performance, collaborate in Agile teams, and engage with clients for requirements and demos.

Design, build, and optimize Databricks-based data pipelines and Lakehouse architectures. Implement ETL/ELT, MLOps, model tracking with MLflow, performance tuning, monitoring, and data governance across cloud storage platforms. Collaborate with architects, data scientists, and clients to deliver scalable, secure AI/ML solutions.